Life With Alacrity

Blog Action Day on Climate Change

Late this evening while catching up on my feeds, I saw for the first time that this year's Blog Action Day is on the topic of Climate Change. This event is sponsored yearly by Change.org. I wish I had known earlier as this would have been a great exercise for my sustainable MBA students at BGI.edu, as they are all creating their blogs this week for my class "Using the Social Web for Social Change".

This is now the second time this week that a significant event on this topic has slipped by me. Apparently on Monday the 19th there will be a Social Media for Sustainability Conference in San Francisco, that seems to have a really good list of speakers. But I only heard about it yesterday.

Part of the problem is that as a blogger I'm not hooked in tight with the sustainability community — clearly because of my BGIedu connections I am sympathetic, but I mainly for the last I've have been writing about the social web or the iPhone. My disconnect demonstrates the challenge of communicating outside your own social circles, both for those trying to create change, and to those that might benefit from the message.

Which brings me to a point that I need to make to my students – we have to figure out how to get ourselves out of info ruts. I teach a technique of Scan Focus Act that is really good at letting you manage your time to read and connect to a larger number of people via blogs, however, if you are too insular, you still may not get the information you need on time. It is through the weak links that we often get our useful information from, and we have to take time to maintain those weak links as well as the strong links to our community that are more easy to maintain as they are more satisfying.

Other then the fact that I learned about it late, I'm reasonably pleased by the example that the Blog Action Day website serves for my students. It satisfies the basic principles of identification and connection, and has a number of good calls for action, the first being to register your blog. The links featuring blog posts with whitehouse.gov, UK prime minister Gordon Brown, and a number of major websites, including the third on the list being in spanish, give the site a credibility. The most recents tab gave the site authenticity. I think I probably would have made the signup process shorter, and had users fill out information later, but it wasn't bad. 

There are a lot of things at this website which will be a good jumping off point for my students to think about as they work on their on blogs on sustainability, and their future Social Change media projects.

Facilitating Small Gatherings Using "The Braid"

I was musing as I was preparing for next week's Intensive at BGI that I have 21 students in my class, an uncomfortable size. That's because it lies between a smaller size where good conversations naturally occur, and a larger size where you can take full advantage of different activities that work well for larger groups.

I talk about this a bit in my Group Threshold and Dunbar Number posts, where I call the group threshold size of between 10 and 24 people the “Judas Number” nadir, or low point. These group threshold nadirs exist when groups are too large for some processes to function effectively, but too small for others to work.

I am particularly aware of this threshold when I host small parties at my home. At 7 or so people everything just seems to work — conversations flow, everybody gets to participate, and everyone has fun. A the numbers climb past 10 I find that I as the host have to work harder, to be more aware of making sure that everyone is having a good time and that no one is left out. At some point as a party gets larger things just begin to flow again, as there are enough people that small groups can form and conversation flows well once more.

I've also seen this at business meetings. When my entrepreneurial companies were small an “all hands” meeting could be incredibly effective. All the issues and ideas got brought up, and everyone felt committed to our decisions. However, as these meeting grew, at some point the “all hands” meeting took too long and started requiring process and rules to be effective. The energy this consumed also diminished much of the efficacy of the meeting.

One tool that I've used to manage these odd-sized groups in the past is what I call “The Braid”. It is derived from a group process called the Café Method, of which The World Café and Conversation Café are excellent examples. In The Café Method, people meet in smaller groups around tables, and then flow from table to table sharing ideas, but ideally keeping each table at 4-7 people. There is an excellent free PDF guide to the Café Method offered by The World Café called Cafe To Go.

The Braid is a little more organized then the more ad-hoc Café Method. When you start a meeting you are given a small card that tells you which table to sit at for each round. Each table is assigned a scribe for each round to take notes at the table, and to report out the notes to everyone who arrives for the next round.

One nice thing about the organization of The Braid is that over the course of a number of rounds you'll have a brand new group of people to talk to during each round. Thus over the course of an hour or so you'll actually get to have a relatively short yet rich conversation with almost everyone in the room, rather than with just a few.

There are different forms of The Braid for different numbers of tables and sizes of groups, but my favorite is the Four Table Braid for groups of a minimum of 16 to a maximum of 28 people. One of the peculiar things about this Braid is that it seems to function well if people arrive at different times. The Braid fills first table A with 4 people so that they can begin talking, then fills table B, C, and D the same way. Once those tables are full, new arrivals are woven into The Braid one at a time until all tables have 5 people, then 6, then the max of 7 for a total of 28 people.

Another nice thing about the Four Table Braid is that no one needs to be the scribe more then once; the task is equally shared among all but the last 8 to arrive in a group of 28. Also, in just 4 rounds with 16 people, 90%+ of the participants have met. With 28 people, you simply only need 5 rounds to match the same 90%+ meeting percentage.

I find The Braid useful for a variety of different situations. The simplest usage is as a group warming and introduction exercise. You need not do more then two or three rounds in order for more than half of the people to have met each other. The Braid is also useful with a focused objective. For instance, I once used it after a game designers' conference, with each table having a list of "game design laws" where the participants were asked to either give an example that was in favor of the law or contradicted the law. It also can be useful in combination with a variety of other group process techniques, for instance after an MG Taylor Take-A-Panel, where each participant first creates a page telling a story about themselves 15 years in the future and then the group uses The Braid to discover common insights. The Braid can also be good before an Open Space or other unconference event.

I am including here my templates for a Four Table Braid. It includes 28 cards for printing on Avery business card paper, 4 table pages with instructions for participants, and 1 page with instructions for the host. I make these available as CC-BY-NC-SA license. I welcome any DTP folks out there who would like to make these documents more functional or more attractive.

A Three Table Braid is easy to figure out by hand, but larger Braids are more difficult. I've never figured out an algorithm for designing these quickly (any math wizzes out there?) so I've posted my spreadsheet for the Four Table Braid for those of you who might wish to figure out how to implement larger numbers of tables. I would love to have a Ten Table Braid as a warm up exercise for a small unconference.

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Four Table Braid by Christopher Allen is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License. Based on a work at www.LifeWithAlacrity.com. Permissions beyond the scope of this license may be available at ChristopherA.LifeWithAlacrity.com. The Power of Conversation graphic is used with permission from The World Cafe Image Bank.

Password Best Practices

Passwords are very important for maintaining your online identity, because they ensure that no one else can access your accounts and do things that you wouldn't do. As such, you should make sure that your online passwords are as strong as possible. This article will provide some general guidelines for doing so.

Multiple Passwords

Note that I said that you want to ensure your passwords, plural, are strong. That's because you'll want at least two. They should both be good passwords, but they should be used in different places.

Use a “non-secure” password for any non-financial websites that you sign up for, such as Facebook and Twitter. Use a different “secure” password for places where your credit card is on file or money changes hands, such as eBay, Amazon, your bank, and your stock broker. Because banks and other financial institutions are more likely to maintain good security over their transactions, reserving a password only for those sites makes it more likely that they will remain safe.

Of course, this could just be the tip of the iceberg. You might want to create a third password for shopping sites, or another one for less reliable sites that you might use. Ideally you would use a different password for every site. That would surely be the most secure, as someone breaking into one site couldn't get into your other accounts — but clearly that is too many passwords to remember. As a compromise, I'll talk shortly about an easy technique to both remember and vary your passwords.

Criteria for Bad Passwords

In a moment, I'm going to suggest an excellent method for creating a secure password. However, if you prefer to use your own methods, be sure to watch out for these common problems which could result weak passwords.

• Do not use obvious words. There was a time when “password” was one of the most common passwords on the internet (along with “root” and “”).
• Do not use words from the dictionary as passwords. Some of the oldest password crackers just dumped the entire dictionary at an account to see if any of them worked as passwords. This doesn't apply just to English either. It's easy enough for a password cracker to use any dictionary, whether it be French or Klingon.
• Do not depend on a dictionary word with simple substitutions. Though I'll talk in a bit about the advantage of substituting letters for numbers, a dictionary word with simple substitutions will be no more secure than just a dictionary word. That's because later password crackers would run not only the dictionary, but also a dictionary with a few substitutions, such as “0”s for “o”s and “1”s for “l”s.
• Do not depend on multiple dictionary words concatenated together. If you were concatenating three or four words, you might be OK, but password crackers were checking two word dictionary concatenations a decade ago.
• Do not use obvious names of people or places you know. Your girlfriend's name, your street address, and your favorite pet's name are all straight out. A password cracker may not be able to guess these (though testing against common names is another strategy used by some), but if someone who knows you can break in by hand, that's no good either.
• Do not write down your password, and especially do not write down your password in an online or computer file. If you picked the best password in the world, it doesn't matter if someone else can easily look at it.
• Do not keep the same password forever. It's pain, but you really should change it every year or two, at least, just in case someone has broken into one of your accounts, and you don't know it.

A Method for Creating a Strong Password

So you've learned a lot about what makes a bad password. What makes a good password? The following suggests one method that you can use to create a password that's not easily breakable — but which is easily memorable.

1. Pick a short phrase, or an obscure but memorable long word. For example “amber waves” or “perspicacious”.
2. Shorten it to 7 characters, such as “ambrwvs” or “prspccus”.
3. Convert a letter other then first to a number. You can use those obvious substitutions here (e.g., A=4, B=8, E=3, G=6, I=1, L=1, O=0, R=2, S=5, T=7), since they're not your only method of security. This might produce “ambrwv5” or “pr5pccus”.
4. The next part is the key trick: use a specific letter from the domain name for the last character for your password and capitalize it. For example, you might add the third o from google, producing “ambrwv5O” or “pr5pccusO” for a GMail password. This ensures that even if you use your password at multiple sites, anyone who steals the password can't use it another website unless they know the trick. You can also use this trick with your computer's password by choosing the third letter from the name you use for the computer, or for a password required for a software application, by using the third letter from the app's name.
5. You should check the quality of your example password at Password Meter -- “ambrwv5O” weight is 54%, which is pretty good for an 8-character password, “pr5pccusO” is 44%, which is OK, but both are significantly better because they will be different at every site.

The same technique can be used with longer words to create more secure financial passwords. These might be easier to remember if you use the first letters from a sentence or poem that you can remember to generate the initial phrase. For example, “My first pet's name was Arthur the Valiant Dog” would generate “MfpnwAtVD”. Again, you convert one or more letters to a number (“Mfpnw4tVD”). 

When you add the domain letters to your secure password, you can strengthen it again by adding multiple letters, possibly to different parts of the password. For example, add the first and last letter the domain name. Thus a Google Gmail password might add a “G” to start and an “E” to the end, producing “GMfpnw4tVDE”. This one rates 70% at Password Meter, but again is actually better because of the site variation.

Also, most financial sites will accept, and some even require, passwords to include a symbol — I don't recommend this with your “non-secure” password as many ordinary sites do not allow symbols, but if you need one, then the following are some easy to remember substitutions: A=@, E=#, I=!, L=!, O=* S=$, or you can just put a symbol between the first domain letter and the passphrase (many sites will not allow a symbol at beginning or end). For example, password above could become “G$Mfpnw4tVDE” which raises this password's Password Meter rating to 90%.

With these two passwords you'll find it very easy to both remember and be secure against most password based attacks.

A High-Tech Alternative

An interesting high-security alternative that works best on webpages is to use SuperGenPass Bookmarklet — it takes the domain name plus a private master password and creates a unique high security password for each website based on a cryptographic hash of the two. It can generate any length of password and you can't really get a password that is more secure, but there is the occasional web page that the bookmarklet doesn't work on. Fortunately, you can save http://supergenpass.com/mobile/ as an .html file to your disk and you can open it anytime to manually create a supergenpass password for a website that you can copy and paste. I've even used SuperGenPass on my iPhone.

Secondary Authentication

Many sites require you to give them additional identification, such as mother's maiden name, the name of your pet, etc. Crackers have broken into various celebrities accounts — such as Paris Hilton and Sarah Palin — by researching this information and asking for a password reset.

You can avoid this danger by treating these authentication requests like passwords. I have a standard word that I use for my mother's maiden name, my pet, etc. They're things that I can easily remember, but no one could figure out. Like the password technique above, I can easily add a letter from the domain. I've had no problem with customer service phone calls to banks; when they ask me for my mother's maiden name I just spell it out my encode word for them.

Be Safe

None of these approaches is perfect, but they significantly raise the bar against any but the most determined cracker from breaking into one of your accounts. The domain letter technique will also make it very difficult for a cracker to break into your more important financial accounts if he gets access to your password from a poorly secured website or masquerades as a legitimate website or email by using a phishing attack.

However, don't ever think that a good password is the be-all and end-all of security. You also have to protect it adequately, and that doesn't just mean not writing it down, as mentioned above. You also must be alert to “social engineering”, where a cracker might call you or email you pretending to be associated with some institute where you might have an account.

Security is a constant game of oneupmanship between you and the black hats. Thus you need to ensure that you're always alert to the current best practices for setting, resetting, and protecting all of your security information on the internet.

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(Photo credit: rattodisabina/ / CC BY 2.0)

Creating Shared Language and Shared Artifacts

We live in a world of conversation, of language; all full of words. Mastery of language requires learning the meanings of thousands of words. The average native English language speaker uses in the realm of 12,000 to 20,000 words, whereas a college graduate would use 20-25,000 words. Shakespeare actively used more then 30,000 words, and his vocabulary was estimated to be over 66,000 words. Yet there are, at the very least, a quarter of a million distinct English words, excluding inflections, and words from technical and regional vocabularies. The Oxford English dictionary defines more then 600,000 words.

But mastery of words is not enough to allow effective conversation.

That is because words themselves don't have meaning; the meaning is provided by the people who use them. Meaning is in the mind, not in the words.

Words also require context, outside of which they may have different meanings. For instance, consider the word "trust". To a banker or CPA "trust" is a property held by someone to manage for someone else's benefit. To a cryptographer it is the confidence in a future outcome based on probabilistic mathematics and past experience. Finally, to the lay person "trust" is about honesty. "Spin" is another example of a word that changes with context; to a weaver it is the production of thread, to a physicist it is a property of elemental particles, to an athlete it is a type of exercise class, and to a politician or public relations professional it is a way to tell a story to sway pubic opinion.

Creating a Shared Language

Every time a new group of people meet together — whether in a team, in a marketplace, or in a community — one of the first activities they must do together is create a shared language. They do this in order to communicate more effectively together, to put a context on the words that they have in common, to construct a shared understanding in their minds based both on available information and their individual diversity of experience.

Don't forget that the linguistic root of communication is the Latin verb commūnĭco  — which doesn't mean "to communicate" but instead means "to share something with someone, to take or receive a part of, to partake, to participate in". Thus the creation of a shared language takes us to the roots of communication.

Without taking the time time to create shared language, groups have a difficult time forging mutual trust. Without a shared language there will be no clarity on mutual goals — whether it involves working together, transacting a trade, or creating something. Without a shared language commitments can be hard to make, and if misunderstood can lead to disagreements. These group formation phases — trust building, goal clarification, and commitment — are essential.

Yet the art of creating a shared language together is not taught. Some individuals and groups do it intuitively while others will just let it evolve naturally over time. However, some facilitators have learned that one of the best ways to help a group form a shared language is by having the group create together a shared artifact.

Using Shared Artifacts

A shared artifact is the creation of an object or shared space that is created collaboratively. It allows the individuals participating to ask the questions: "Is this what you mean when you are talking about this? I use these words, so suppose we change it to this? Is that what you mean? Does this reflect our new shared understanding?"

Examples of shared artifacts include Watson & Crick's Tinker-Toy DNA model. Each scientist would work on the model separately, then use grad students to carry the model around to his partner to express certain ideas. Both Compaq Computer and Southwest Airlines were reportedly established after their founders wrote their ideas down together on a table napkin, another shared artifact.

Both of these examples show an important factor in shared artifacts — if the shared artifact is not constrained then it will be too large or complex for the group to reach some measure of completion. Finishing the shared artifact really helps establish trust and the connections between the participants.

A shared artifact is also useful because flooding someone with information and terms gives no assurance that the recipient has gained knowledge of the subject. Instead, the act of creation confirms to both parties that the knowledge was successfully assimilated.

Another advantage to creating a shared artifact is that it isolates any problems to the task at hand. Often there are differences in status, purpose, or perspective that can get in the way of group formation, but a focus on a common task of the creation of a neutral shared artifact allows those issues to come later as the participants develop the trust and shared language required to talk about those tough issues.

The best facilitators know what kinds of shared artifacts work best for different groups under different circumstances. Sometimes a shared artifact is just a model of a process drawn on a white wall. Often it is a creation of a mission statement or joint objectives. I personally like taking old mind maps and trying to recreate them anew with more recent knowledge.

The Future of Shared Language

The nature of shared language is changing in the 21st century. The conjoined social networks in the blogosphere — via Facebook, Twitter, or the attendee-focused Unconference — cause new terminology and new language to form ever faster. I've personally seen words like "retweet" and "attribution" gain important contextual meaning within my social networks. As with any shared language, newcomers have difficulty discovering their meanings only by osmosis.

Tagging is another means by which shared language is rapidly expanding. Certain words are gaining context through common use at Delicious.com, Technorati, Flickr, and other tag-enabled web sites.

To a certain extent, all of these new shared languages are built upon shared artifacts. Twitter, Facebook, Delicious.com and others sites each create constraints on how language is shared and with whom. However, there is little purposeful social design being applied to these new shared languages. Though there may be shared artifacts, they are not purposefully facilitated.

Will these increasingly organic shared languages prove better than more purposefully created ones or worse? Is social language facilitation the next big thing in social network? Or is there just not enough space for it within the tightly constrained social artifacts of the internet? These are questions that we as social software technologists need to address as the future of the internet increasingly becomes the present of our social groupings.

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(I learned the concept of Shared Language in 1990 from Michael Schrage's book Shared Minds: The New Technologies of Collaboration. It is out of print, but there is a new edition retitled No More Teams!: Mastering the Dynamics of Creative Collaboration. The use of a modeling language to facilitate group formation I learned from Matt Taylor (@worthyprojects) of MG Taylor Corporation, though the use of the term shared artifacts and approach is my own. I make passing reference to the early stages of team formation ("trust building", "goal clarification", "commitment") which come from the Drexler/Sibbet Team Peformance Model. The poem is by excerpt of a larger work by John Campion and is reprinted with permission — the work reflects the poet's Ecotropic concerns and are part of his third book-length poem Medusa. Look at the work under the Medusa Project link. The table napkin photo is from an excellent post on The Idea Napkin by Morry Potoka and is also reprinted with permission. The Watson-Crick photo is public domain, and the Life With Alacrity graphic was produced using Wordle.)

Teaching "Using the Social Web for Social Change" at BGI.edu

Starting next week I will be teaching a course at the Bainbridge Graduate Institute on the topic of "Using the Social Web for Social Change".

BGI offers an MBA and Certificate program for professionals to learn how to build enterprises that are financially successful, socially responsible and environmentally sustainable. Students have to learn everything that they'd have to learn in an ordinary MBA program — profit and loss, how to read a balance sheet, business plan creation, macroeconomics, quantitative analysis, corporate strategy, how to manage and motivate people, and a basic understanding of all the components of business such as operations, marketing, distribution, sales, etc. In addition, BGI student have to learn green and sustainability topics — the triple-bottom line, environmental accounting, sustainable energy, social justice, systems thinking, organization change, right livelihood and much more.

That broad a curriculum doesn't give students a lot of room for electives, but the MBA program allows for students to take one 3 credit hour course. This year students can choose from three: one course on social responsibility, a second course on climate change and carbon trading, and my course on the social web.

The BGI pedagogy (a new term I have just learned, meaning "teaching method") is a mixed hybrid of online sessions along with a number of very intensive in-person classroom sessions. This allows the MBA student to continue working while taking classes in either a 2-year or 3-year program.

Students kick off their BGI experience at Channel Rock on Cortes Island in British Columbia, where the live for a week at an off-the-grid wilderness retreat, where they get the chance to experience and practice sustainability. Over the course of the year students and faculty meet in intensive classroom sessions for a 4-day weekend once a month at the  IslandWood environmental learning center on Bainbridge Island near Seattle, Washington. Between sessions, the classes utilize a variety of online distance-learning technologies such as Elluminate to support student learning.

I like this hybrid format because it fits my ideals of group formation — bonding and team building work best in the immersive, in-person experience, yet the online technologies allow students to have greater flexibility, deeper focus, and more control over their engagement while remote. BGI offers students both.

When the class is complete, I plan to offer the syllabus, course plan, presentations, etc. online as open courseware, so that other schools can use these materials as a basis for future classes. In the meantime, expect to see some more posts here over the next few months.

Creative Commons Posts "Defining Noncommercial" Report

Last year I participated in a survey followed up by a focus group on the topic of Noncommercial Use, in particular around the context that about 2/3rds of the Creative Commons licenses extant use the NC attribute, such as in CC-BY-NC.

Defining "Noncommercial":  A Study of how the Online Population Understands "Noncommercial" Use
http://wiki.creativecommons.org/Defining_Noncommercial

The topic is somewhat of a sticky one, as there are many competing interests. There are content creators who wish to profit from their work, there are other content creators who don't want anyone to profit (even themselves), and of course there are content creators who want everything to be free provided you share free content back.

There also is not agreement on what noncommerical means. There are some clearly commercial uses, but there are also various type advertising and sponsorship and use by non-profit or education institutions where money changes hands (such as a card at a museum gift shop). Finally, there is use in news or criticism where users feel that they are not restricted due to the rules of fair-use.

I'm not sure that there is anything definitely "new" in this report, but there is some consensus and some interesting facts:

• The vast majority (73%) of creators define “commercial use” as a use where money is made, 76% of content users agreed.
• 33% of content users thought that individual use was noncommercial use, whereas only 19% of the content creators believed so.
• Content creators rate uses by individuals as being less commercial (89%) – unless the user is a professional who earns money (35%)
• 13% of content users thought that fun, enjoyment, entertainment and artistic use was noncommercial use, whereas only 3% of content creators believed so.
• 52% of the content creators don't believe that content users understand the noncommercial provision, and 43% believe that content users don't respect the term.
• 50% of the content creators have been contacted about licensing their noncommercial content, 24% of the content creators have attempted to contact another creator about appropriate use of a CC license.
• There is a lack of agreement on a lot of edge cases of noncommercial use. For instance, some feel cost-recovery is acceptable noncommercial use, money exchanged hands for a charitable use would be noncommercial, or use by a for-profit company where no money changed hands would still be noncommercial.
• There is some interesting analysis of what people might be willing to change their mind about. For instance, before focus group participation only 8% thought that use for charitable purposes for social good would be noncommercial, but after the focus group 17% did.

All in all an excellent report, with lots of good data in it for further investigation. If you are involved in user-generated content, offer users creative-commons licenses, or are a consumer or provider of commercial content online, I recommend you take the time to understand these issues more deeply.

My personal take on this report is that the noncommercial provisions of the CC license need more clarification and there needs to be more user education. In addition I feel that Creative Commons also needs to look at the commercial use side of the problem. I appreciate the recent efforts toward a CC Plus metadata, but it isn't enough.

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For instance Creative Commons should take a principled stand on what exactly "fair use" is; make it easier for those who offer NC licenses to also offer a standard commercial license for common uses; and possibly creating a standard for what "fair rights" are in commercial license (i.e. fair to both the content creator and the content user).

There are also problems in the area of attribution, as all Creative Commons licenses except Public Domain have the BY provision. These get particularly difficult when you have a remix of content from many creators. There's also difficulty in the fact that it's not stated what places attribution must be listed in. For instance, can you do a movie or a podcast with remixed content, but have the attribution credits be a link? Or must they be credits in the media itself?

All are interesting problems that I hope Creative Commons will address in the future.

Community by the Numbers, Part III: Power Laws

In my first article in this series I talked about community numbers: how the sizes of groups ultimately affect their success (or failure). However what I discussed only offers up the most rudimentary explanation of the dynamics, and that is because typically not all of the members of a group are equally involved.

In order to better define who constitutes the tightly-knit "participant community" upon which the group thresholds act, we have to study power laws which let us measure the intensity of individuals' involvement in a group.

An Overview of Power Laws

The best-known power law is probably the Pareto principle, which is otherwise known as the "80/20 law." It's been overused throughout the years; Pareto's actual law only said that 80% of the wealth would be held by 20% of the population.

However, it offers a fine example of how power laws work. They generally describe a discrepancy between intensity and population: inevitably, some people do a lot more of the work in any social situation. Other examples include Zipf's Law, which suggests that the frequency of a word's usage is inversely proportionate to its ranking among words (making the second ranked word appear half as much, the third a quarter as much, etc), and the long tail, which talks about selling a very large number of items in a very small individual quantity.

For online communities, which have been the focus of most of my studies on the topic of community sizes, I've found that the participation inequality power rule is very apt.

This term comes from Will Hill of AT&T Laboratories, who said, "A major reason why user-contributed content rarely turns into a true community is that all aspects of Internet use are characterized by severe participation inequality." It's often equated with the 1% law, though I like to be more precise and say that 90% of an online community tends to be lurkers, 9% tends to be intermittent participants, and 1% tends to be active participants.

These values heavily influence online community sizes that are larger than the tightly-knit communities group thresholds that I previously discussed.

Power Laws & Group Thresholds

When I wrote about tightly-knit communities in my first article, I didn't consider the degree of participation. That's certainly an entirely valid model for some types of groups. Corporations, for example, ideally should be entirely filled with active participants, while Skotos' online game Castle Marrach also fits into the category due to the implicit requirements it creates for participation. There are some challenges to grow this type of community, since you're only searching for a specific type of high-energy participant — but they can be overcome if you offer sufficient incentive (such as a salary or a lot of internal feedback).

However, most communities, and in particular, online communities, will not fall into this category, and thus when we're looking at group thresholds, we have to measure them against the number of active participants, not against the number of total members. Thus, for groups which allow for non-participation, we'll often measure 10% (or maybe 1%) of the group size against the group thresholds.

RPGnet, one of the community sites that Skotos runs, offers a good example of this. We regularly see monthly uniques of approximately 200,000 users. However we probably have about 20,000 active registered users, confirming the lurker:participant ratio. When we recognize that only 2,000 of those are particularly active participants and that they're divided upon 6 successful forums, we start to see how community numbers that actually match the group thresholds can gel.

You can reverse this approach and look at active participants first. During some recent consulting for a local non-profit organization with 60 active online members, I was able to infer that their broader community was around 6000, which turned out to fairly accurately predict the total number of people who came to their live events over the course of a year.

Generally, this logic can be applied to a community of any size. You first measure whether it's an all-participant community or one that matches an existing power law, and then you use the corrected community number to truly measure which of the group thresholds may apply to it.

Power Laws & Leaders

The power laws can also help you to measure the number of leaders in a community. Inevitably all of your participants will become leaders of some sort, while your high-level participants will become the top-tier leaders.

I noted this in my first discussions of group threshold. In a group of 7 members, you can reasonably expect to have one higher level participant, and thus the one leader that we saw naturally appear. Similarly in a Judas group of 13, there's the opportunity for more than one leader to appear, creating the possibility for the first hierarchical conflicts.

Understanding your count of leaders can help you see how to grow groups. For example when I first created iPhoneWebDev I had to do an immense amount of effort to grow the community. This is because with Participation Inequality I had to grow the group by 10 members before I got the least amount of help increasing the content of the group and I had to grow it by 100 members before I had someone who was doing as much work as I was to create content.

At 100 members, with my first active participant, we continued to grow, but we were both were working hard and felt rather lonely.

I finally saw the group stabilize, then take off on its own, when it hit 600-700 members, and that shows how beautifully the power logs work hand-in-hand with the group thresholds. With 700 members, I could reasonably expect there to be 7 leaders. In other words, I had a committee of leaders: the perfect size for a starting working group.

From my experience with other online groups, if the iPhoneWebDev grows to over 10,000 members, I can expect that there will be some transition issues. As the core active community members exceed 100 people I will start having some Non-Exclusive Dunbar Number problems, typically social contract failures. These can be solved by either adding some hierarchy (appointing some people to be official "staff"), or by starting to break the group into sub-communities.

Varying the Power Laws

In my first article, I noted that it's possible to expend additional energy to make tightly-knit groups able to function effectively at non-optimal sizes. It is similarly possible for the values of the participation inequality sized groups to change by expending more energy. Conversely, a drain on energy may decrease this ratio.

For example when I used to run AOL forums I would frequently reward first-time participants with free time (at that time worth $5 an hour) if they asked good questions or offered valuable input. CompuServe similarly offered constructive feedback by telling users how many responses they'd received to a new comment when they logged back in, encouraging them to leave lurker status. More energy in the community — driven either by the moderators, good social software design, or by a greater commitment by its members — can allow you to increase the active participant percentage, maybe times 2, or even 4, but even with a lot of effort not by an order of magnitude.

As a group grows in size, I believe the participation inequality worsens. A huge Yahoo! group with a million members might have moved from a 90/9/1 ratio to 95/4.5/.5. I suspect this is because the energy required to change the participation inequality numbers is so large as to not be economical.

There are also some interesting interrelations between the numbers of people at the various levels of participation. Though discovering 100 new members has a good chance of adding 10 new participants, 1 of whom is very active, my experience has been that things trickle-down in the other direction as well: that adding 1 new high-level participant can lead to the creation of 9 medium-level participants and 90 lurkers (though don't let that suggest that all of your effort should be expended on the high-level participants only).

Looking at Participation Inequality

Here is a close look at four online communities, using the quantcast.com metrics service, where you can see some participation inequality in action:

From this you can see a typical online community site shows the normal 90% 9% 1% participation inequality. RPGnet shows a slightly better then average participation inequality due to its longevity and the quality of the community. ObesityHealth shows evidence of a great community with its 4% active participants, probably because you have to be very committed if you are going to have bariatric surgery. Last, an example of relatively unhealthy community that is unable to sustain its active participants.

You do have to be careful when analyzing quantcast numbers if you see active participants of greater then 6% — in almost all cases if you look deeper it is because there is some restriction that keeps people from lurking, either a fee or some other type of gateway, causing a distortion in the statistics.

Conclusion

Multiple factors influence the success (or failure) or community. As we saw in my first article on community numbers, the first factor is the differing group thresholds of community sizes. In my second article, I show that personal limits on the number of people you can have intimacy and trust with is an important factor. In this article I show that larger groups are subject to the power law of participation inequality, causing a small fraction of a community to be subject to group thresholds. In all three articles I show how expending energy can allow you to change the numbers, but with limits.

I hope this discussion of community numbers will give you some tools to look at the communities you are in, or are trying to build, and to better understand how to make them more successful.

---

Some other posts about the Dunbar Number and group size issues:

• 2004-03: The Dunbar Number as a Limit to Group Sizes
  (also some really good comments)
• 2005-02: Dunbar Triage: Too Many Connections
• 2005-03: Dunbar, Altruistic Punishment, and Meta-Moderation
• 2005-07: Cheers: Belongingness and Para-Social Relationships
• 2005-08: Dunbar & World of Warcraft
• 2005-10: Dunbar Number & Group Cohesion
• 2008-09: Community by the Numbers, Part One: Group Thresholds
• 2008-11: Community by the Numbers, Part II: Personal Circles

My bookmarks to various papers and websites on this topic are available at delicious.com/ChristopherA under some of the following tags:

• participation inequality - more specifics on participation inequality.
• participation inequality - everything I have on the topic of power laws, including participation inequality.

If you have any links on this topic that you would like to share with me, tag them for:ChristopherA and I'll take a look.

Illustrations by Nancy Margulies. Many thanks to Shannon Appecline and F. Randall Farmer for their assistance with this series.

Community by the Numbers, Part II: Personal Circles

In my previous post, I talked about the limits on sizes of tightly-knit communities. These group limits are closely related to a number of interesting personal limits, and are often confused with them.

Unlike the group limits, personal limits actually measure something different: the number of connections that an individual can hold. They're yet another thing that you must consider when thinking about communities of people.

Personal Limits

The Support Circle: This is the number of individuals that you seek advice, support, or help from in times of severe emotional or financial stress. In most societies, the average size of an individual's Support Circle is 3-5. The people are the core of your intimate social network and most typically are also kin. In sociology papers this is often called the "support clique".

The Sympathy Circle: This is larger then the Support Circle — it is the number of people that you go to for sympathy and also those people whose death would be devastating to you. The Sympathy Circle typically is in the range of 10-15 people, but can vary widely from as few as 7 to as many as 20. The Sympathy Circle often may be made up of kin, but usually includes some peers as well.

In sociology papers the Sympathy Circle is also known as a "sympathy group", but I wanted to avoid the term "group", as it is implies that all the members of a Sympathy Circle are connected. Instead, members of your Sympathy Circle will have additional people in their own Sympathy Circles that are not part of your own.

An interesting issue with the Sympathy Circle is that as a personal limit, 10-15 is a typical size. however, if you bring them all together in one place, they will likely become a Judas-Number-sized group, with all of the problems associated with that size.

The Trust Circle: These are the people that you have some type of intimate connection to. One study measured it as the people that you would send a family Christmas card to, while another simply tested emotional closeness.

In pre-Friendster days the Trust Circle would be those people that you considered your "friends", however today the meaning of that term has begun to change. In my own usage, your Trust Circle are people that you have strong ties to and that in some measure you can trust. I have also called the Trust Circle your personal "intimate social network".

The size of different individuals' Trust Circles can vary widely (40-200), but some studies show that the mean is on the low side of 150. This has led a number of researchers to compare this number with the Exclusive Dunbar Number of 150. However, I believe that this is a mistake; they are related, but in today's society members of your Trust Circle are rarely in the same mutual group.

The Emotional Circle

I personally define your Emotional Circle as the total number of people that you can have some type of non-mutual emotional connection with, most likely spread across numerous groups of all sorts. You "like" them in some way, but do not necessarily have to have strong ties to them.

In academia this threshold is called "social channel capacity". A study using two different methods to estimate, both suggest that it falls right around 290. However, I like to describe this number as "just short of 300." As I wrote in Dunbar Triage, many people confuse this number with the Dunbar Number (and in fact I have in some of my older pieces). However, like the Trust Circle, it's a distinct entity.

Emotional Circle size can vary quite a bit from individual to individual. Some people might have half the average capacity, and others considerably more — which is much more variation than you see among the sizes of smaller personal thresholds.

Some of those variations are individual, but some are societal. As I wrote in Cheers: Belongingness and Para-Social Relationships, I believe that our modern era of television causes us to create para-social relationships with imaginary characters who we nonetheless become emotionally involved with, and thus might reduce our social channel capacity.

Is our Emotional Circle smaller today because of TV or is it higher because online communities can help to remind us of our emotional connections to other people? That's a topic that probably deserves more study.

An interesting point to make is that the people who are in your Emotional Circle, but are not in your Trust Circle, are your "weak ties" in social network terms. What is important about weak ties is that studies show (pdf) that opportunities and knowledge flow to you much more through weak ties than through the more insular strong ties of your trust circle.

The Familiar Stranger

Outside of our Emotional Circle is a larger, more tenuous circle: those people whose faces you recognize, but who you know nothing more about. These are your "Familiar Strangers".

Studies show that the percentage of familiar strangers in your vicinity has a real impact on your willingness to take risks. If you are in a new place with no one that you recognize, you'll avoid eye contact and will generally be unwilling to approach strangers. In a place where there are a lot of people that you've seen before (say in your favorite cafe, at a conference, or in the lunchroom of a large company), you'll be much more willing to take risks, such as asking questions, or sitting down next to someone to eat lunch.

I haven't been able to find any studies to show how many people that we can recognize, but for some people it is much larger than the number of people in your Emotional Circle, probably well over a thousand. However, there is also a lot more variance: some people are face-blind or near face-blind, and have a difficult time even recognizing friends.

There could also be some interesting research looking more closely at social network software. I find it fascinating that the professionally-oriented social network LinkedIn resisted supporting photos in profiles for so long yet ultimately failed, as well as how other social network software companies have attempted to require "real" photos of people rather then allowing "fakesters" or avatars.

Crossing the Circles

I've used the term "circles" throughout this article because it's a great metaphor for these levels of personal involvement. They can literally be thought of as concentric circles of people getting further and further away from an individual.

However, if you want to consider them with an even more graphic bent, think of these circles as the ridge lines of a topographical map. An individual sits at the center, and around him lie many other people, fading slowly away as the distance increases.

Winding through these topographical lines, like forests or rivers, are geographies of physical and emotional connection.

Kin are one of the most interesting geographies, because they lie all across the map. There's a clump of them in the innermost circles, but there are also many who lie in the realm of Familiar Strangers, including those cousins and great-aunts who you only see at family gatherings, and whom you know nothing about.

There are also forces being exerted upon the circles, acting like gravity to draw people together. They are the forces of trust, influence, and more. Their pulls are greatest toward the center, across your Circles of Support and Sympathy, but as people move farther away, these forces drop off quickly.

Thus, though I've described them as circles, with strict boundaries, we should also see these personal connections as fluid entities, a regular ecosytem of personal community.

Conclusion

Whereas the group thresholds that I discussed in my last article define the limits placed on community group size, the personal limits described herein instead define the limits placed on how many people an individual can know with various degrees of intimacy.

Perhaps there are societies where these two things might be the same. A true survival community might contain everyone a person knows, and thus he could draw out all his personal circles across that community canvas. However, in our modern era they're much more likely to be distinct, with an individual interacting with the members of his circles of acquaintances through numerous different group communities.

With this bifurcation of personal and group community limits, we have to briefly stop and ask a few questions. How do they relate? What can personal limits tell us about efficient community creation? Does founding a group upon a personal circle make its growth easier or harder? Conversely, what type of communities lead naturally to the creation of intimate circles?

Herein I've simply outlined personal thresholds as a contrast to group thresholds. The exploration of how these limits interact is worthy of additional studies.

In my next article "Community by the Numbers, Part III: Power Laws", I will talk about how both group thresholds and personal thresholds have a role in larger, less tightly-knit groups.

---

Some other posts about the Dunbar Number and group size issues:

• 2004-03: The Dunbar Number as a Limit to Group Sizes
  (also some really good comments)
• 2005-02: Dunbar Triage: Too Many Connections
• 2005-03: Dunbar, Altruistic Punishment, and Meta-Moderation
• 2005-07: Cheers: Belongingness and Para-Social Relationships
• 2005-08: Dunbar & World of Warcraft
• 2005-10: Dunbar Number & Group Cohesion
• 2008-09: Community by the Numbers, Part One: Group Thresholds

My bookmarks to various papers and websites on this topic are available at delicious.com/ChristopherA under some of the following tags:

• personal circles - everything I have on the topic.
• familiar strangers - those people you recognize by face.

If you have any links on this topic that you would like to share with me, tag them for:ChristopherA and I'll take a look.

Illustrations by Nancy Margulies, photo by davitydave. Many thanks to Shannon Appecline and F. Randall Farmer for their assistance with this series.

Community by the Numbers, Part One: Group Thresholds

We often think of communities as organic creatures, which come into existence and grow on their own. However, the truth is they are fragile blossoms. Although many communities surely germinate and bloom on their own, purposefully creating communities can take a tremendous amount of hard work, and one factor their success ultimately depends upon is their numbers.

If a community is too small you'll often have insufficient critical mass to sustain it. Conversely, if it's too large you can end up with a community that's too noisy, too cliquey, or otherwise problematic. These optimal and sub-optimal community sizes appear in strata, like discrete layers of rock. For a community to advance from one strata to the next often takes immense energy.

We can analyze these community sizes in three ways. In this first article I'm going to talk about numerical group thresholds that have been observed in various sizes of tightly-knit communities, while in its sequel I'm going to talk about personal thresholds and how they relate to group thresholds. In my final post, I'm going to consider how power laws and inequalities of participation further complicate these simple values in the creation of larger communities. Together these three articles constitute what I call "Community by the Numbers," a theory of community size.

Though I'm going to point to some studies which support these numbers, in general my goal here isn't to try and prove this theory of community size numbers, but rather to lay the theory out completely.

Tightly-Knit Group Thresholds

Groups can clearly exist at any size, from a partnership of two, on upward. However what I'm going to write about here are the threshold values: the ideal numbers where a community seems to function best, and the less than ideal numbers at which a community begins to grow unstable, remaining so until a new threshold number is reached.

I'm also specifically talking about groups that are both tightly-knit and participatory communities. Clearly Ford Motor Company, with 250,000 employees, doesn't match any of these group thresholds. But any self-contained community within Ford probably will (and in fact, it will probably be either a "Working Group" or a "Non-Exclusive Dunbar Group", both terms I'll explain below). Similarly, a non-corporate community that doesn't require everyone to participate won't work quite the same as a community that does require participation from each member (though that's again the topic of the third article in this series).

7, "The Working Group". This community size probably runs from about 4-9 members, but 7 is a pretty good average, and one that shows up in multiple studies. This number may well relate to the general rule of seven (original paper), which suggests that 7 is a number that the brain can easily and intuitively comprehend.

It has become increasingly clear that a tightly-knit group of 7 is the first group size which is truly an optimal community size. Groups below this size can function effectively, but risk not having enough manpower to deliver a result that everyone is happy with, or having insufficient viewpoints to avoid group think.

Seven is not only an optimal size for a wide variety of corporate and government committees, it is also a healthy size for a small business and even a good size for a party of close friends. More importantly, 7 is a very comfortable group size as it "feels" relatively natural. At this size members find it easy to get to know the other members of the group, and they're able to function well together in a very intuitive and organic fashion.

An interesting example of this group size is the modern infantry "squad", which consists of two fire teams of 4 people, and a squad leader, for a total of 9 people. Each fire team is is large enough to function on its own, but together the group of 9 can still have effective small group dynamics.

It is typically at this size that the first signs of leadership in a group informally emerge, but the leadership usually isn't overbearing at this level, nor does there tend to be any rebellion against it — perhaps because the group may be too small to elicit multiple leaders.

13—"The Judas Number". A group size of 13 doesn't represent a threshold ideal value, but rather a threshold nadir. It is one of the points where groups can change behavior and risk becoming dysfunctional. There's one of these nadirs beyond every group threshold, where the previously harmonious group dynamics become more difficult. I've chosen to highlight this specific number because it's a point that small communities often hit, particularly as entrepreneurial organizations try to grow above their startup beginnings.

(I should note that 13 isn't a precise number, but rather one offered because it's in the right range and because it's poetically easy to remember. The exact number occurs somewhere between 9 and 25, but I suspect it is worst in the range of 12-15.)

In a group of this community size no one ever feels like they get a fair share of time. Studies show that at this size participants underestimate the amount of time they contributed to the conversation, and thus will come out feeling like they were unfairly ignored despite having a fair share of the conversation. Groups of this size risk people being lumped into categories and ceasing to be trusted as individuals. In addition, problems start with the development of "too many chiefs," yet there is not enough enough variety of non-chiefs for them to direct. Furthermore, multiple leaders may struggle for hierarchical status, increasing the conflict in an already troublesome group.

If your community is unfortunately stuck at this nadir, one of two things usually occurs.

Most commonly, the group shrinks. This could be because participants unhappy with the group dynamics abandon it; or it could occur in a more organized way with the unwieldy large group breaking into two or more smaller groups. For example, a terrible group of 13 could become two more functional groups of 6 and 7.

Alternatively, more energy could be expended. This could be in the form of more formal organization, rewards for participation, or more time to be casual and socialize in order to shake off the tensions of this size group. Though these efforts don't usually change the size of the group, they can improve its dynamics.

Energy could also be spent to help push the group up to the next threshold. Though this could occur naturally — for example if the group focuses on a topic of particular interest that causes new people to continually be added. In addition, in order to grow a group to a new threshold it often requires the efforts of more than one leader to succeed.

A group size of 13 isn't necessarily bad, just more difficult. Anthropological studies show that primitive hunting tribes often temporarily broke into "bands" of this size — my presumption is that the value of having that many people hunting together outweighed the social costs of the group. It is interesting that most juries are made up of groups this size. I believe that the social dynamics of this size of group with all new members creates some tension among the jurors, which may serve justice to make sure that all sides are considered by the jury without falling into groupthink. However, from my experience, the interpersonal conflict in a jury can also slow down the deliberation process and cause much frustration among the participants.

50—"The Non-Exclusive Dunbar Number". More properly this group size falls in the range of 25-75 participants, but it seems to feel the most natural in the range of 50-60. Studies of the sizes guilds in online games support this hypothesis. For instance, based on graphs of the guild sizes in Ultima Online, groups have a median of 61 members. Similar numbers hold true in studies of a more recent game, World of Warcraft.

I call this value the "Non-Exclusive Dunbar Number" because it matches the lower end of a threshold that Robin Dunbar set for group sizes. However, at this size it applies to mostly non-exclusive groupings, which includes the above mentioned online guilds, many employee communities, and the majority of social gatherings that manage to rise above the size of a Working Group. Groups of this size can be serious or take up a lot of time, but in general they are not exclusive — they don't tend to be the only group that individual participants are involved in.

90—"The Dunbar Valley". As Non-Exclusive Dunbar Number communities grow, they reach a point where increased time obligations and the noise of socialization required to keep the group cohesive requires a much more serious commitment from the participants. Like the Judas Number, the Dunbar Valley is a threshold nadir where more energy is required to keep a tightly-knit community together;  either the community agrees to a higher level of commitment and grows to the next level, or the community splits apart.

I've found this to be true when growing a small business — where it is too small for any middle-management, but the sub-groups are too large for one person to manage effectively. I've also seen this with more ephemeral groups, such as when a small conference that worked well at 60 participants tries to grow and finds at at 100 participants they can't sustain a high enough intimacy level.

Another illustration of the Dunbar Valley is the history of the ancient Roman "century", a grouping that was originally 100 soldiers. However, as the years went by, centuries tended to decrease in numbers to only include 70 or 80 soldiers. This might well be due to Non-Exclusive Dunbar constraints: even in a very devoted group of military men, there was still the need for relationships with other century groups, with support staff, and with camp followers, ultimately lowering the attention that could be spent on the century itself.

150—"The Exclusive Dunbar Number". Robin Dunbar got much of the discussion of group thresholds started with his article, "Co-Evolution Of Neocortex Size, Group Size And Language In Humans." However, as I've written previously, and as I've described in this article, Dunbar's group threshold of 150 applies more to groups that are highly incentivized and relatively exclusive and whose goal is survival.

Dunbar makes this obvious by the statement that such a grouping "would require as much as 42% of the total time budget to be devoted to social grooming."

The result of the grooming requirement is that communities bounded by the Exclusive Dunbar Number are relatively few. You will find hunter/gatherer and other subsistence societies where this is a natural tribe size. You'll also find these groups sizes in terrorist and mafia organizations.

Clearly, as we step up toward higher group thresholds, more and more time is required to simply keep the group going. You see this in depictions of mafia life — in the TV series The Sopranos a lot of time is spent dining, hanging out, and drinking together. That is part of that 42% social grooming time required for that intense of a survival group.

It is possible for a large company to force groups up to this size by expending lots of energy (which is to say money) to keep it healthy. Apple did this during the invention of the Macintosh, the first OS X operating system, and the iPhone, but the intensity required of such large teams is not sustainable for long periods of time.

Without that extra energy, few modern tightly-knit communities can reach this threshold, or else can't hold it for very long. Instead they fracture into groups of individual interest (even if they continue to "meet" in the same real-world or online forum), which are more than more likely to be bounded by the Non-Exclusive Dunbar number.

Given the difficulty in even arriving at the Exclusive Dunbar number, it may well be the highest limit of all for a tightly-knit community. Beyond this limit, communities are less cohesive, less trusted, and less participatory (and the topic of my third article in this series.)

Conclusion

There are many different ways to measure groups, and one is by counting its members. As I've discussed here, the number of members can have a huge impact on whether the communities are successful or not. Thus, as community organizers, social software engineers, game designers, or as sociologists interested in community dynamics, we must ultimately consider group thresholds and group nadirs; to understand how to create cohesive communities, rather than groups that fly apart.

In my next article I'm going to talk about thresholds that are personal, rather then group-oriented.

---

Some other posts about the Dunbar Number and group size issues:

• 2004-03: The Dunbar Number as a Limit to Group Sizes
  (also some really good comments)
• 2005-02: Dunbar Triage: Too Many Connections
• 2005-03: Dunbar, Altruistic Punishment, and Meta-Moderation
• 2005-07: Cheers: Belongingness and Para-Social Relationships
• 2005-08: Dunbar & World of Warcraft
• 2005-10: Dunbar Number & Group Cohesion
• 2008-11: Community by the Numbers, Part II: Personal Circles

My bookmarks to various papers and websites on this topic are available at delicious.com/ChristopherA under some of the following tags:

• group threshold - everything I have on the topic
• workinggroup - on small groups such as committees
• dunbar number - on larger groups such as tribes

If you have any links on this topic that you would like to share with me, tag them for:ChristopherA and I'll take a look.

Many thanks to Shannon Appecline and F. Randall Farmer for their assistance with this series.

New Blog for Ephemera

This blog has been quiet lately as I've been doing a lot of work in the last year on the iPhone. I've been speaking at conferences like eComm 2008 (presentation, video from panel), writing an book on the iPhone with my co-author Shannon Appelcline called iPhone in Action: Introduction to Web and SDK Development (first two chapters free), and I am one of the organizers for the upcoming iPhoneDevCamp 2, a MacHack style conference on August 1st-3rd, and I am working on some social software apps for the iPhone.

I've been reluctant to post too many of these off posts on this blog, as I like the length, quality and high-signal-to-noise ratio of the posts that I've written for this blog. I do plan to continue to offer more social software and social media posts, including followups to my Collective Choice articles, as well as updates on my popular Dunbar Number posts. But I don't want to spam my readers here with notes on iPhone Apps, my thoughts on movies, circuses, the odd conferences I speak at, etc.

So I've been trying to figure out how to cover some of the other things that I am up to without loosing my readers here, so decided to a create a new blog for my shorter and more transitory thoughts: Christopher Allen's Ephemera Blog. So far I have posted:

• Max 9 pages, thus Max 144 Apps on iPhone OS 2.0
• First Look at AirMe App for iPhone
• Trying Out TypePad's Blog It Web App
• iPhone TypePad App Second Pass
• iPhone TypePad App First Look
• Ephemera Blog

The RSS feed for this blog is here .

If you are interested in some of the other things I am looking at, you can follow my del.icio.us bookmarks, or read my Google Shared Items, watch my Twitter posts, or see them all combined together in either FriendFeed or Plaxo Pulse.

In Seoul for the Social Web

I'm in Seoul, South Korea this week for the 13th Global Forum on Business Driven Action Learning and Executive Development, where I'm presenting on the topic of the how to get involved with the Social Web.

My presentation is an offshoot of an odd sideline of mine, executive blog and social web coaching. Basically, many times over the last couple of years I've been asked by colleagues and friends to help them with the social web. I've always been honored to spend the time to teach them how to blog, better manage the noise of the web by using a feed reader, how to participate in social networks, and how to improve their personal brand.

Increasingly, the social network of their peers is now asking me to help them to do the same for them. So I've been doing this more and more over the last year on a consulting basis as their social networks appear to be saying saying that I have a lot to offer.

I've twice now been out to Cincinnati where I've been working with Drew Boyd at Johnson & Johnson, where I've been coaching him on his blog and personal brand. He has been blogging now for almost six months at Innovation in Practice with some success. Now he is referring me to other executives at Johnson & Johnson who need similar coaching, or need strategic advice on how to deal with specific social web initiatives within Johnson & Johnson.

Most recently, Drew has asked me to join him in Seoul to speak at the Global Forum, which is a worldwide gathering of executive trainers. There I am presenting a synopsis of what I teach, and how they can begin to learn how to teach their staff how to do the same. My trip has been sponsored by Johnson & Johnson, so it has been a lot of fun to be here. I get to both dive into deep discussions of methodologies for teaching inside business, as well as learn about the Korean and other international business cultures and how they are different from the United States.

During the evenings I've had a chance to wander the streets of downtown Seoul. It is very different then wandering though streets in Europe, not only because of the different culture and language, but also because all of the signs are in Hangul, the korean character set. Very few signs use the roman alphabet, so it is often very difficult to figure out what is what without walking in. Like Japan, there are some signs in English to represent a brand or a style, but not many. Even China has more signs in English then Korean's do -- the last time I was there I was surprised by how almost every important sign was in both Chinese and English, so much so I was beginning to learn Chinese language characters just by association! Despite the language problems everyone is nice and it feels safe to wander in these neighborhoods.

I return on Monday, and I'll make a copy of my final presentation available here.

iPhoneDevCamp and Hack-a-Thon

I feel privileged and honored to have been part of the iPhoneDevCamp this last weekend. Over 380 iPhone developers came out to the Adobe Campus in San Francisco to help each other make the best possible web pages and webapps for the iPhone.

I was the keynote speaker on Saturday and Master of Ceremonies for the MacHack-style Hack-a-Thon Demo on Sunday.

At the Hack-a-Thon almost 50 iPhone web applications were demonstrated to an enthusiastic audience. Take a look at Tilt, a game that takes advantage of the iPhone's motion sensor, PickleView, which is a same-time live baseball game enhancer, and The Pool, an attractive social game of water droplets hitting a pool. What is remarkable about these applications is not just the quality, but that each of them was written over just the weekend by a small team of 3-4 people who hadn't met each other before Friday!

Prizes were awarded after the Hack-a-Thon based on the spirit of openness, contribution, sharing, and participation. Prizes included 3 iPhones and some very expensive Adobe software. In particular Joe Hewitt, of Firebug fame, was honored for his positive contributions, generous spirit, and wonderful iPhone UI example code. During the demonstrations, more than one person praised Joe, saying that his assistance, his code, or his debugger made their apps possible. Personally, I think about one-third of the web apps presented used some of his code.

Building on my experience with the same-time collaboration tool SynchroEdit, and the Skotos web-based games, I worked remotely with Kalle from Sweden and Erwin from Kansas to present an AJAX chat application called iLace. I am particularly proud of how well this little web application performs and how well it works using the iPhone UI. In particular, I think its melding of text entry and chat message receipt and its response to changes between portrait and landscape modes are very good examples of what can be done for chat on the iPhone. Source code is available!

My keynote presentation slides are now available in .pdf and .mov. I'm told a live recording of the session and an .mp3 will be available soon.

Over the last few weeks an online developer community that I started at WWDC called iPhoneWebDev has grown to over 650 members. It's now the best place to get online support for building iPhone web pages and webapps. I'd like to keep the momentum from the iPhoneDevCamp going forward on this list, so if you are interested in developing for the iPhone, check out the example code and join the discussion today!

Getting Ready for the iPhone

I've been excited about the web capabilities of the upcoming iPhone for some time. As a reluctant laptop user ("oh, my aching shoulders"), there is real appeal to me in a better portable web browser. I have tried most of the PDA and cellphone browsers to date, and none offer more then a poor cousin to the web that we experience on the desktop.

Instead, the iPhone offers a desktop-class browser. There is no transcoding, nor any subset of HTML such as WML. Full web pages are rendered in the small display, and when you "double-tap" with your finger the section you touch is expanded to a more readable size. The video available at the Apple website shows this capability in use.

Because of the iPhone's upcoming July 29th release, I decided to participate in this week's Apple WWDC conference for Macintosh developers. There a number of announcements about the iPhone were released, and a number of technical sessions on the iPhone and iPhone-related technologies were held. Together the iPhone demonstrations at the public keynote and other demonstrations throughout the WWDC offered some real promise for when the phone is released on June 29th.

The biggest announcement at the public keynote was that there will not be an SDK for building native iPhone apps; instead, the only way for third parties to get involved is to create web applications optimized for the iPhone. This came as a big disappointment to the majority of developers participating at WWDC. However, as someone who has been involved lately in creating AJAX/Web 2.0 apps, I was less unhappy.

The other significant announcement at the keynote was that a Safari 3.0 beta for both Mac and Windows was being released and that a third Safari platform would be released on July 29th—inside the iPhone. This means that web 2.0 applications created to work with Safari on the Mac will likely also work on the iPhone.

Since SynchroEdit, an open-source simultaneous web editor (in the style of SubEthaEdit) for Firefox that I produced last year, is one of the most sophisticated AJAX/Web 2.0 applications, I dug deeper at various WWDC sessions to see if it might be possible to make SynchroEdit work on the iPhone.

One of the biggest things that SynchroEdit needs in order to function is DOM Mutation Events. At a party for WebKit (the open source code underpinnings of Safari's web renderer) and in questions after a session at WWDC it was confirmed that these are available to Safari 3.0 and presumably the iPhone.

The other key ability that SynchroEdit requires is WYSIWYG editing. This was terribly broken in Safari 2.0, but I saw many demonstrations of it working in Safari 3.0, so I don't anticipate any problems with this.

SynchroEdit also requires AJAX and in particular the XMLHttpRequest function, and the keynote clearly said that this was available.

The final thing that SynchroEdit needs is the ability to keep the browser at readystate==3, i.e. not "finish" sending the page, so that we can continue to interactively pass updates to users as they arrive, without creating a new connection for every message. It is not clear if this will be supported on the iPhone, but there are ways to work around it.

So, in principle, it appears that we should be able to make SynchoEdit work on the iPhone. I am not sure that many iPhone users need SynchroEdit, but as an example of a very sophisticated web technology that should work on that platform, it shows the potential for what might be possible.

Because of this technological capability I've decided to begin investigating what type of social software apps could be highly useful on the iPhone and that aren't being served by the existing web 2.0 community. I am also going to continue investigating the technical issues of developing web apps for the iPhone

If you are interested as well, I invite you to participate in the new iPhoneWebDev community. It should be a great resource for everyone interested in getting in on the ground floor with this new web technology. I have also begun tagging relevant web pages in del.icio.us with the tag iphonewebdev—I hope that others will begin to use this tag as well.

I have quite a bit more I'd like to write about specific iPhone technology, but unfortunately I have to wait until the WWDC confidentiality expires on June 29th with the release of the iPhone, so keep an eye out here for more details.

Collective Choice: Experimenting with Ratings

by Christopher Allen & Shannon Appelcline

[This is the fourth in a series of articles on collective choice, co-written by my collegue Shannon Appelcline. It will be jointly posted in Shannon's Trials, Triumphs & Trivialities online games column at Skotos.]

Last year in Collective Choice: Rating Systems we took a careful look at eBay and other websites that collect ratings, and used those systems as examples to highlight a number of theories about how to make rating systems more useful.

We suggested three main methods for improving rating systems:

Granular Ratings: Based on the clumping of ratings to high values, we believed that ratings could be made more useful by increasing the size of a rating scale. Most rating scales are 5-point ranges, so we suggested a 10-point range instead.

Distinct Ratings: Raters can be somewhat arbitrary in how they rate items, varying both from each other and even from themselves (usually over multiple sessions). Thus we believed that providing explicit statements of what each number meant could improve ratings.

Statistical Ratings: Finally we stated that in low volumes ratings could be biased by various quirks of data entry, either malevolent or not, and that ratings could be improved with strong statistical methods being used to polish up data and automatically keep "bad" data in line with "good".

In the year since we wrote that article we've decided to practice what we preach and have rolled out an entirely new rating system called The RPGnet Gaming Index. We've applied all of the above theories and thus far it looks like they're not only working, but that they're actually providing better rating systems than previous ones we've used at the RPGnet site.

In this article we're going to step through the data we've collected from this experience and see how it applies to our theory: first by looking at our previous RPGnet rating system, then by looking at the new system, and finally by by examining the data from these two systems and comparing their results. We've also run into some unexpected troubles along the way, and we'll talk about that too.

The RPGnet Reviews System

RPGnet is our gaming site for tabletop roleplaying—games like Dungeons & Dragons and Vampire: The Masquerade. We purchased it in 2001 from the original owners. One of the benefits of RPGnet was that it had a very large community. As of today it sports one of the top-100 forums on the Internet, with over 1000 simultaneous users regularly logging in. However, because of its maturity, we also inherited many existing systems.

One of these was the RPGnet Reviews System which gave individual users the ability to review gaming products—mostly role-playing games, but also board games, books, DVDs, and a smattering of related products.

Most of these reviews are submitted by average readers who just want to talk about a product that they like (or don't), though a fair percentage are instead submitted by staff reviewers. (Overall at least 26% of our reviews are based on publisher "comp" copies, and thus may be considered largely professional, while the other 74% may or may not be.) The large community size of RPGnet applies to the Reviews System as well: currently it features 8,505 published reviews.

Looking at the RPGnet Reviews through our three filters we find the following:

Granularity. The ratings from our existing reviews aren't as granular as we'd like. We have a theoretical scale of 2-10, but that's based upon a Style rating of 1-5 and a Substance rating of 1-5.

Rating	Style	Substance	%
1	81	225	1.8%
2	732	651	8.1%
3	2364	1777	24.3%
4	3618	3525	42.0%
5	1709	2326	23.7%

Approximately 90% of raters rate only with values of 3-5, and thus our scale is more limited than the 2-10 range would indicate. 42.9% of reviews further rate Style and Substance exactly the same, suggesting that not everyone sees a difference between these two elements. On the whole this scale isn't as a bad as a singular 5-point scale, but it also isn't a real 10-point scale, and the two orthogonal types of comparison don't necessarily provide a coherent description of a product.

Distinctiveness. Conversely, the review ratings are fairly distinct because the Review System provides an explanation of what each rating number means. For example the five Substance ratings are: I Wasted My Money (1); Sparse (2); Average (3); Meaty (4); Excellent(5). The descriptions could be better, but hopefully they connect to some users in meaningful ways, and help them to rate consistently.

Statistics. Our review ratings have no statistical basis. These values are used entirely unfiltered.

On the whole, the existing RPGnet Reviews embodied slightly less than half of what we wanted to see in a rating systems: some improvement over a simple 5-point scale; some effort put into making individual ratings distinct; and nothing statistical.

There is room for improvement, however, as we'll see when we analyze this system more fully.

The RPGnet Gaming Index

Our newer system is the RPGnet Gaming Index. It doesn't supersede our Reviews, but instead offers a complementary look at the roleplaying field. The Index is essentially an RPG industry database. It contains individual entries for many different gamebooks—currently 5248—and allows registered users to rate each of them. Those ratings are then turned into averages by various mathematical formulas on a nightly basis and the roleplaying games in our index are then ranked.

The large size of RPGnet has allowed us to very quickly turn our ideas of a Gaming Index into reality. Just six months after release we have:

• 5248 well-written Index entries
• 5908 different editions
• 4240 authors
• 4478 covers
• 360 different game systems
• 345 series
• 10142 individual ratings

Most of the ratings are clumped around the best and worst games, with many less popular games unrated as of yet. Four different items have at least 80 ratings each (Call of Cthulhu, Exalted, Nobilis, and Unknown Armies). Our average rating is 6.79. Ratings above 7.82 are in the 99th percentile, ratings above 7.21 are in the 90th percentile, and ratings below 6.53 are beneath the 10th percentile.

(For more info on the creation of the RPG Index, and how to encourage user generated content, see Shannon's articles, "Managing User Creativity", Part One and Part Two.)

The RPGnet Index also handles some unusual situations, such as when a game book contains other game books as part of an anthology or compilation. For instance, the 8-book compilation In Search of Adventure has a composite rating of 6.57 which is partially based upon the individual adventures that make it up.

Granularity: The first thing we did was provide a 10-point scale for this new system.

Distinctiveness: We also made sure each point of the scale was clearly defined. Currently the points of our scale are: Worthless (1), Poor (2), Some Flaws (3), Almost Average (4), Average (5), Above Average (6), Good (7), Very Good (8), Outstanding (9), and One of the Best Ever (10).

We made some mistakes in our original release of our "distinctive" titles, and we discovered this had real effects on the user input, telling us that these title labels are meaningful to users.

First, we initially labeled 6 as "average", to mirror the rating system for our existing Reviews, rather than setting 5 to be average. But as we noted in our first article, people like to be nice, and thus they tend to rate on the good side of a scale. Changing the label for our definition of average from 6 to 5 has slowly started dropping the average of all ratings down as a result (providing more breadth, a topic we'll talk about more shortly).

Second, two of our original distinctive titles were at odds with the others. Our original "2" value said that the game had "a few useful elements" and our original "9" value said that it was the "best of the year". The 2 was much more specific than any of our other terms and the 9 created a comparative query that was very different from anything else. Overall our ratings conformed to a bell curve centered between 6 and 7, but we saw very clear dropouts in our curve at 2 and 9, telling us that we'd made mistakes in those terms, and that people were less willing to use them as a result. Since we've made the change to our current set of titles those two discontinuities have disappeared.

Statistics. Finally, we fully integrated statistics into our new Index by using two main methods: bayesian weights and trust.

We explained bayesian weights pretty fully in our previous article. Here's what we said then:

The idea behind a bayesian average is that you normalize ratings by pushing them toward the average rating for your site, and you do that more for items with fewer ratings than those with more ratings. The basic formula looks like this:

b(r) = [ W(a) * a + W(r) * r ] / (W(a) + W(r)]

r = average rating for an item

W(r) = weight of that rating, which is the number of ratings

a = average rating for your collection

W(a) = weight of that average, which is an arbitrary number, but should be higher if you generally expect to have more ratings for your items; 100 is used here, for a database which expects many ratings per item

b(r) = new bayesian rating

Say three "shill" users had come onto your site and rated a brand new indie film a "10" because the producer asked them to. However, you use a bayesian average with a weight of 100, and thus 3 ratings won't move the movie very far from the average site rating of 6.50:

b(r) = [100 * 6.50 + 3 * 10] / (100 + 3)
b(r) = 680 / 103
b(r) = 6.60

We implemented bayesian weights exactly as we'd detailed, but with a lower weight of 25. Since then we've accrued over 10,000 ratings in the database, and we can probably start thinking about cranking that weight up, another topic we'll return to.

Our trust-based algorithms suggest that some ratings are better than others, and should thus be more trusted (and thus more weighted when we calculate the average rating of an item). Though bayesian weights have been used before, we're not aware of other systems that weight ratings based on trust.

The calculation of trust is very simple:

Weight = 0 if #ratings(user) <= 2
Otherwise Weight = #ratings(user) / 50 to a maximum of 2
Weight *= 2, to a maximum of 4, if the user included a comment

This was based on the idea that the average good rater would rate 25 different items and the average great rater would rate at least 50. Additionally, we believed that ratings with comments were more likely to be thoughtful than those without.

That, overall, is a quick picture of what we've done with the RPGnet Gaming Index. Some of these ideas were laid out from the start, and others have been tuned as we progressed.

So how did we do, particularly in comparison to our existing RPGnet Reviews System?

The Comparison

One of our goals in improving rating systems has been to widen the range of possible input. As we noted earlier we discovered that 90% of our RPGnet Reviews Ratings were in the 3-5 range, and only 10% in the 1-2 range.

Generally, we can measure the success of widening a range by seeing whether the average rating of a database moves toward the true average. For the purposes of a 10-point scale from 1-10, that's a desired value of 5.5. That generally means we're looking for our average rating to decrease because people tend to rate high.

The following table compares the average results of Reviews ratings and Index ratings.

Database	Average
Converted Reviews	7.25
Massaged Reviews	7.29
Unweighted Index	7.10
Weighted Index	6.78

Here's what the categories in the above chart represent:

Converted Reviews: The Style + Substance of the Reviews, converted from its 2-10 scale to a 1-10 scale:

$rating = avg($style) + avg($substance);
$rating = ($rating * 1.125) - 1.25;

Massaged Reviews: The Style + Substance of the Reviews, with Substance given double weight over Style because we think that more closely reflects the intentions of the reviewer, converted from its 2-10 scale to a 1-10 scale:

$rating = (average($style) + 2*average($substance))/1.5;
$rating = ($rating * 1.125) - 1.25;

Unweighted Index: Index ratings exactly as users have entered into our Gaming Index:

$rating = average($index-rating);

Weighted Index: Index ratings adjusted by the weight of each individual rating, which is based on user trust and inclusion of comments:

$rating = average($index-rating*$index-weight)/average($index-weight);

Our average rating—which is our criteria for success—decreased somewhat from the Reviews System to the Gaming Index and it decreased much more dramatically when we introduced our trust systems.

The following chart shows the a typical example of how review and index ratings differ, using the venerable Dungeons & Dragons Player's Handbook as an example:

For this book the median ratings from reviews-only is 8, and the median from index-only is 7. A one-to-two point drop in median rating from reviews to index was consistent in all of our most-rated games other than those which were a rated a "10" in both places.

We believe that this initial success of our unweighted Gaming Index can be attributed to the slightly better granularity—a 10-point scale versus two 5-point scales—and our improved distinctiviness—based on better naming of the rating levels. The veracity of this will ultimately be played out as the Index grows.

However we have no doubt that our statistical approach to the index data, when we moved from our unweighted Index to our weighted Index, is providing even better results. We had theorized that users who input more and who include comments would provide "better" data, and by our criteria of the average of the ratings moving toward 5.5 that seems to be borne out. The following table looks at the information a bit more precisely, by comparing average ratings as total number of ratings increases over several ranges:

# of Ratings	Average w/Comment	Average w/o Comment
1-2	8.55	8.88
3-24	8.08	8.16
25-49	7.32	7.11
50-99	7.14	7.03
100+	6.17	6.99

This table fairly definitively shows that base maxim: that the breadth of the ratings, and thus their quality, increases the more ratings a user makes. The improved quality of ratings with comments is less definitive. Among the vast mass of users the two values are pretty close, and sometimes the reverse of what we expect, but for the best and the worst users, ratings with comments seem to be better than those without. This latter point is another one that we'll have to continue to monitor as the Index grows beyond its current total of 10,000 ratings.

The other major element of our statistical approach to the Index is our bayesian weight. The following chart shows a top-ten chart for roleplaying games calculated via four different methodologies: our Reviews; our Index with no weighting; our Index with a 25 bayesian weighting (as it currently stands); and our Index with a 50 bayesian weighting:

#	Reviews-Only	0-weight Index	25-weight Index	50-weight Index
1	Delta Green: Countdown	The Chronicles of Talislanta	Delta Green: Countdown	Delta Green
2	Nobilis	Wildside	Spirit of the Century	Delta Green: Countdown
3	Castle Falkenstein	Devil's Due	Delta Green	Unknown Armies
4	Vimary Sourcebook	Lodges: The Faithful	Unknown Armies	Call of Cthulhu
5	Liber Servitorum	Apocalypse	Call of Cthulhu	Nobilis
6	Ork!	Earthdawn Gamemaster's Compendium	Nobilis	Spirit of the Century
7	GURPS Russia	Into the Badlands	Pendragon	Over the Edge
8	GURPS Reign of Steel	Earthdawn Player's Compendium	Over the Edge	Pendragon
9	Cudgel's Compendium	Chronicle of the Black Labyrinth	Mutants & Masterminds	Mutants & Masterminds
10	Corum	The Spell Book	Pulp Hero	Vimary Sourcebook

We actually did do a little bit of statistical analysis on the Reviews because on our first try to produce this chart we got a random clump of reviews that were 5/5 from a much larger pool, so we further ordered them by descending total count of reviews, and as a result you're seeing a better selection of ranked reviews than a truly unstatistical sampling would allow. We did the same for the unweighted Index (which clumped a number of results at "10"), except we further ordered items at the same weight by decreasing number of views (another statistical decision).

Clearly, deciding which of these lists is "right" is a much more subjective measure than the mathematical analysis we were able to apply to earlier problems. However, most roleplayers would tell you that the unweighted Reviews and Index lists are terrible. The top 5 items in the Reviews list actually aren't bad for a starting list of good games—but only because we did the aforementioned statistical ordering. Before that we just had a random listing of gaming items. Even with our attempts at quickie statistical analysis the unweighted Index is still quite bad, with only Talislanta regularly showing up on other "best" lists.

The problem is the ability of one person to come in and rate an item a "10" (or a "5"/"5"), thereby making that item more highly rated than any item which has an actual consensus of ratings. Of our unweighted top Reviews only the top three had more than 2 reviews and the rest had 2. Not surprisingly those top three were the best fits to a typical top-ten list. Of the unweighted Index only the top three had more than 1 rating, and the rest had 1. Our single good pick was in those top three.

Our 25-weight Index, which is what we currently use, has been generally accepted by the RPGnet community as a good marker of what's good and what's not. However there have been two items on it which some percentage of people disagree with: Spirit of the Century and Pulp Hero. It's instructive to see that when we increase to a 50-weight Index Spirit of the Century drops (even more notably than depicted here, because its actual rating changes from .01 from first place to .16 from first place) and Pulp Hero disappears entirely.

The questions of what to set your bayesian weight to, when to increase it, and what maximum value to set it to are all relatively unstudied and thus we don't have good answers to them. As we pass 10,000 ratings we're considering upping the bayesian value to 50. We expect that 100 will be our ultimate value when the Index is fully mature, however if we increase the weight too far an older, less rated game will never be able to get enough weight to get out of the doldrums.

Conclusion

We're by no means done with this ratings experiment. Though we've pleased and impressed with the growth of the RPGnet Index thus far, by next year we hope that the Index will include the vast majority of all games in print (as opposed to somewhat less than half now) and that our 10,000 ratings will grow to 50,000 or more. This will allow us to offer even more definitive answers to our questions.

In the meantime we're still mucking with our statistics and facing new problems.  Some of the newest:

• What to do about drive-by ratings: Our trust algorithm does a good job of making drive-by ratings, where a publisher points his audience to an item in our site, mostly irrelevant, but there's some concern that they could have more effect in the long run.
• How to incorporate our review ratings in our index ratings: It seems a shame to waste the thousands of reviews that have been written—and indeed currently they're calculated into a composite rating we use in the Index—but we're realizing that people have very different purposes for writing reviews and inputing ratings, which may result in some of the upward skew we see on the review side of things. Ultimately we need to decide whether they're just too different or whether our statistical massaging is enough to incorporate those reviews into a composite Index rating.
• How to pick some of our numbers: As we already noted we don't have good formulas for when to choose which bayesian weights. Likewise we've been guessing at which values to use for the trust-based weighting of our raters. Originally we set our desired rating count to 100 for good rater and 200 for great raters, but we've since dropped those to 50 for good and 100 for great based upon the real numbers of ratings that users were making. Again, we'd prefer to derive an actual formula for this type of calculation

Shannon has discussed some of these issues more in his recent article More Thoughts Abour Ratings.

Despite unanswered questions, we still feel good about the basic ideas we laid out in our article last year. We have no doubt that giving our ratings a statistical basis has dramatically improved them and evidence thus far suggests that both granularity and distinctiveness have been helpful as well.

---

Related articles from this blog:

2005-12: Systems for Collective Choice

2005-12: Collective Choice: Rating Systems

2006-01: Collective Choice: Competitive Ranking Systems

2006-08: Using 5-Star Rating Systems

Related articles from Shannon Appelcline's Trials, Triumphs & Trivialities:

#192: Managing User Creativity, Part One

#193: Managing User Creativity, Part Two

#196: Collective Choice: Ratings, Who Do You Trust?

#198: Collective Choice: More Thoughts About Ratings

Speaking about SynchroEdit at WikiWednesday

I will be speaking tonight at WikiWednesday on the topic of Same Time, Different Place Editing, and will be demonstrating SynchroEdit integration with MediaWiki and EditThisPagePHP.

If you are interested, see you tonight (Wednesday) at 6-8pm, at Socialtext.