Category: Social Software

At the Sunlight Foundation event, several tools were using wiki and wiki-like features. Eugene Kim and I led a session on effective wiki practices. One of the people at the session was at a traditional NGO, and wants her group to be more open, potentially using wiki for distributed information gathering around their core coverage. One of the barriers to wikification is the fear of “anyone editing” and the potential impact on quality. The NGO benefits from the specialized nature of its information. There are 10,000 regular users of the database, which feels like a lot to the NGO. But with a community of 10,000 readers, one might expect to start small, and build to a group of contributors in the hundreds to low thousands, which is quite a manageable size. Also, the “watchlist” feature of larger wikis enables subcommunities of specialists to watch and protect the areas they care about most, and develop social norms to maintain quality. Another cultural barriers to wikification was that the staff considers readers — mostly journalists — as an audience, and not yet as a community. The main cultural transition is to consider the readers a participatory community, and to evolve from a private, letter to the editor model to a peer contribution model.
The barriers faced by this NGO seem common to the sector. Traditional public interest organizations see their audiences as traditional journalists and legislative staff. Their content is not-very-accessible databases and pdf reports; the websites have little about the people involved in the organization; the membership, when their is one, is seen as a source of credit cards and petition signers, but not organizers and active participants. NGOs need some new cultural concepts to take advantage of the new tools.
There were some interesting wiki ventures at the event, and new in the world. CongressPedia was at the event. One of the strengths of that model is the ability to build a persistent and easily google-able reference source. Another Sunlight-funded tool, Open Congress, is aggregating bill and blog data to provide more visibility into the bill-making process. The foks building the tool plan to add a “wiki” feature for collaboration. Not sure how that would work, that seems like an invitation to edit wars and disinformation because of the frequently competitive nature of the legislative process.
I’m most excited about the potential of the Adopt a Committee project of the Daily Kos community. This is starting with a community of likeminded folk to grow and protect the information; enables distributed information gathering and group memory for a large number of people with mixed amounts of time; and seems like a great way to shed light on the committee process where bills take shape. Perhaps the role models for successful use of read/write web tools will be new groups that aren’t burdened by traditional top-down-media orientation. If the dot com revolution is a model, startup organizations will pioneer new techniques, which will eventually get rolled into the ordinary way of doing business.

Ross asks for a meme aggregator that shows him what his social network is looking at. In order for this to be really useful it needs a feature that Amazon had in its apparently now defunct purchasing ciricles. You could look up what people in Austin, or people at Cisco were reading. But the algorithm stripped out the most popular products, and showed the things that people in Austin had distinctively in common. So you wouldn’t see the non-information that a lot of people watch the superbowl, but you would see that a lot of people saw a particular Jon Udell podcast.

Rashmi Sinha hits the nail on the head. Being social is more about sharing than declaring. Sharing meals, sharing music, sharing gossip and news, sharing activities, all of these kinds of shared experiences are the stuff of social life, beyond the “hello” and the tribal handshake.
Rashmi’s insightful presentation on “Design for Social Sharing” explores the design patterns of “second generation social networks that put objects at the center: tagging, video, news creation”. Design patterns include passing on a cool video, tagging and rating. Social sharing apps combine personal social value. Tagging a link helps me remember it, and helps others find it too. Creating a playlist or group of pictures helps the person who makes the list, and other who come later.
One insightful pattern is sensing the presence of others. The is the magic of recent changes in a medium-sized wiki, where you can have a window into what your colleagues are thinking. The conventional wisdom is that “presense” means synchronous presense — I can see that you are there and I can interrupt you if I want to. Asynchronous presense is differently good, you can see the flow of others’ activities without interrupting.
Rashmi Social Sharing as a “second generation” of social networks, beyond the first-generation of explicit tools like Friendster. I think the generational terms are more about the hype cycle than what’s been going on. While the Friendster fad flared, LiveJournal and Flickr fostered community and fun, and MySpace skyrocketed. Now, the design patterns and the nature of social apps are better understood – it’s not just about saying hello.

Sunday’s Washington Post is running a version of the mainstream media “concern troll” article about Wikipedia. Parents and teachers are dismayed that kids are plagiarizing homework assignments from Wikipedia. The answer comes from a new product from AOL, called “Study Buddy”, which, er, contains authorized material for kids to plagiarize from? The answer, of course, that kids are supposed to be learning critical thinking skills. They’re not supposed to be plagiarizing articles from the World Book Encyclopedia either. They are supposed to be learning to look up more than one source.
The article sniffs that “User-created content, such as entries found in Wikipedia, the open-to-most online encyclopedia, comes with varying degrees of trustworthiness.” Of course, and human-created content comes with varying degrees of trustworthiness.

One of the persistently frustrating things about Amazon’s reader reviews is that they don’t have permalinks. Reviewers can’t respond to other reviews, or even bring in references to reviews of other books. This prevents people from talking to each other. It prevents flamewars, and it prevents community.
Recently, Amazon has added several new “features” that borrow from the forms of social software. A “plog” looks like a weblog. It is a listing, in reverse chronological order, of posts about products you’ve seen or expressed an interest in. Unlike a “blog”, which consists of posts the author has written, a “plog” is a marketing newsletter, with messages from authors and others who are trying to sell you things. Apparently the right to write is bestowed by Amazon upon slected authors or marketers. The recipient of this unnatural hybrid has very little over the content. You can make a comment, and comments even have permalinks. But there is no venue inside the Amazon sprawl to use these links to write back. The user doesn’t have obvious ways to write or link. This is the opposite of user-generated content, it is content inflicted on the user.
In the same family of mutant social software is Amazon’s wiki feature. The so-called wikis appear near the bottom of a well-shaft-long scroll of various product description and review features. If you log in with a username and credit card (!), you can edit a page about that product. I need to upgrade my credit card, apparently, in order to see if the wiki even has a linking feature. It is clear from perusing the top wikis that linking isn’t part of the idiom. People who are writing collaborative commentary about, say, the XBOX, aren’t building a rich , interlinked history and knowledgebase of the games market, trends, and technology, unlike the WIkipedia entry. Instead, the Amazon “wiki” is a short and shallow review that happens to have been written by more than one person. The Amazon XBOX wiki doesn’t even have it’s own link as far as I can tell, all you can do is get to the xbox page and scroll all the way down. This is the opposite of the design pattern of atomic entries, identified by links, and interconnected by links, that allows the Wikipedia entry to grow and deepen with links to Microsoft, components, games, market trends, and related information.
The problem with Amazon’s reviews is that the absense of links inhibits the creation of community. The wikis are antithetical to the concept of building a rich knowledgebase using shared vocabulary as links. The plogs don’t allow user-generated content. In all of these “features”, Amazon’s interface designers have borrowed the appearance social software but missed the meaning and the social dynamic that makes the whole of blogs and wikis to be greater than the sum of the parts.

Here’s the anecdote that was most telling about the wrong track taken by Affective Computing, the book by MIT’s Rosalind Picard about the digitizing of emotion.
Picard writes about giving a lecture as part of an elearning program. She was troubled by the fact that she could not read the emotional responses of people in the audience, unlike a physical lecture hall, when you have visual signals of interest. Her suggestion was to wire the audience, and get a digital readout of the emotions.
In recent years, conferences and remote meetings have developed a different mechanism to read the response othe participants. A simple text chat enables people who are engaged to show and share emotions with smiles praise, questions, or heckling. In great presentations, the backchat is dead silent, as the audience is spell-bound.
Unlike a physical room, where even someone silent may reveal emotional signals through physical signs of boredeom, excitement, or anger, a backchat reveals nothing from someone who is silent. That’s not quite true – someone who wants to telegraph excitement or displeasure in a 3D meeting room will also use backchat signals. In small groups, silence in a teleconference and backchat is also revealing. A group leader can ask someone who is unusually silent to say what they are thinking.
Another big difference is that in a lecture hall, or a remote presentation with backchat, participants have substantial control over the emotions they display. Picard’s hypothetical mood thermometer might pick up on involuntary emotions, or emotions the participant might want to hide. A participant might be feeling angry at a family member, or lustful for a fellow member of the audience, or exhausted because of a small infant at home. Picard’s hypothetical mood-reader would transmit those emotions to the lecturer.
Picard herself notes that all known emotion-detecting technology can be fooled by skilled humans. So emotional surveillance in the virtual classroom would lead to unnatural emotional repression. what’s weirder, the mood thermometer is one-way — the lecturer can see the mood of the audience, but the audience can’t read each other. Backchat is very different from the mood thermometer. Like same-place emotions, backchat allows participants to feed on each other expicitly. This difference comes directly from Picard’s belief that affective computing is “personal” — her model doesn’t include the social aspects of much of human emotion.
The backchat model can be extended to include emoticons, color feedback, and other signals to share emotions with other participants and the leader. These nonverbal signals can complement text chat; allowing people to do the thing they’re good at, combining thoughts and emotions in communication.
Picard’s theories rely on complex tools to automate emotions, rather than on simpler tools that allow people to share thoughts and emotions with each other. I think her theories are misguided, in an interesting and revealing way.

I’ve found three slick websites supporting greenhouse gas policies. This Climate Choices site from the Union of Concerned Scientists, focused on the California Legislative session is nicely designed, links to the bills, has videos and action alerts. But no obvious people, and no direct feedback.
This national site from Environmental Defense focuses on getting signatures in support for the languishing McCain Lieberman bill in Congress. It has a petition and videos, as well as gizmos you can put on your site, including banners, instant message icons, and PC wallpaper. But no humans, no way to provide direct feedback, no obvious way to meet fellow activists. I can see that over 100,000 people have signed the petition in California. Uh, yay, I guess.
This National Resources Defence Council has an action alert, a postcard to send, and a place to sign in and see the history of actions you’ve taken. . But no humans, no way to provide direct feedback, no obvious way to meet fellow activists. I can see that over 100,000 people have signed the petition in California.
These campaigns use the internet as if it were a fancier form of direct mail. A beautiful brochure, with some more widgets and animation. No opportunity to take advantage of the ability to meet to the people behind the scenes and to talk to each other. None of the messy, potentially unpredictable consequences of actual political organizing.

Jimmy Wales, the founder of Wikipedia, gave a talk at Stanford last week. The bits that struck me from the talk were about the human model of community that makes wikipedia work.
Jimmy described two models of online communities. In one model, people are ants. Information emerges from the unwitting contribution of the masses. Individuals are not powerful. In this model, reputation is a number. In the second model, people are a community, a few hundred active volunteers who know each other and interact based on kindness and trust. In this model, reputation is human.
Despite the high traffic – 5B page views per month at last count, Wikipedia is a tight community. 50% of edits are added by 615 people, and 73% of edits by 1746 people.
Wikipedia is a network of encyclopedias in different languages. The “tipping point” when an encyclopedia has enough critical mass to succeed is a community of 5-10 people, producing about 1000 articles. An encyclopedia gets reallyl useful at 500,000 to 100,0000 pages.
Jimmy gave two stories that showed the value of open access and community-defined process.
Say you’re going to open a restaurant, and you’re going to serve steak. There are steak knives that can be used to kill people. What do you do? You lock people in cages (he shows a very sad gorilla in a small cage on a concrete floor) By increasing barriers the barriers to doing bad things, you prevent people from doing good things.
Wikipedia has a very simple and flexible model for voting about whether a page is to be kept or deleted. It is just a wiki page, where participants note whether they believe the page should be deleted. Then an admin makes the decision. More weight is given to evidence that a topic is valid — if there are 8 people who think it’s hoax, and two people who prove with citations that the topic is valid, the page is kept. Programmers regularly ask whether they should write a voting widget, and Jimmy says no.
The wikipedia model is less common than the traditional software model, where access is restricted as much as possible, and permissions are restricted as much as possible. As wikis become more popular, some people gravitate toward the familiar pattern to manage content by keeping people out. It’s inspiring to look to wikipedia’s overwhelming success for lessons of the benefit of access, flexibility, and human community.

I understand Squidoo a bit better now that the fact that it’s Seth Godin’s company has sunk in. In the social software equation, the individual motivation is self-promotion, and Godin is hoping that others will be as entertaining in their quest for fame and fortune as he is.

I ran across while preparing for a panel on “tagging 2.0” at sxsw. They sell a faceted classification product used for information retrieval. They did Facetious, a cool del.icio.us mashup which applies facets to delicious tags.
In order to describe their hack as part of my talk on collaborative tagging, I wanted to know how it works. Does the software create the facets? Does the software suggest facets, which are then selected and edited by human administrators? Or do humans create the facets for Siderean to fill in?
I ordered collateral from the website — needed to fill out a form for each piece of collateral, and talk to a salesman first. The collateral didn’t answer my question — it was all benefit/result marketing, with nothing about the software itself. So I emailed the salesguy. He said he could only answer the question if Socialtext was seriously interested in partnering with Siderean.
So I didn’t include Siderean in the presentation. Does anyone have a clue how the software works?