What, you want more yammering on activity streams? My friend, look no further.

I got to thinking: what is the scanning behavior for users looking at an activity stream? More specifically, when scanning a stack of activity feed items, what visual cue is the user looking for to indicate that a certain feed merits more attention? And what does that imply for how activity feeds should be designed?

If we’re to go by the current trend in activity feed designs, author, or, more specifically, an iconographic depiction of author, is most important. The designs of Twitter, MySpace, and Facebook feeds all feature a profile photo prominently on the left-side of each activity feed item (and remember, the eye scans left-to-right, so the picture is what people see first).

Twitter feed with author pics as main differentiating characteristic.

MySpace feed, also with author pics as main differentiating characteristic.

This makes sense for these apps, since the content of these feeds is mostly homogeneous. With Twitter, merely status declaration. With MySpace: Same. Thus, one can scan and select to read based on how much one actually cares about the author of the activity bleep.

With Facebook, though, it’s a little more complex, as users are also posting links to images, Websites, and whatnot, in addition to simple declarations of status.

Facebook feed, also with left-hand author images, but more variance in what appears in the feed (links, video, images, etc.).

That heterogeneity of content starts to make the feed more visually confused and difficult to scan. In fact, I would argue the various graphics and links start to overshadow the simple status declarations.

Which brings us to Friendfeed. When it launched, FriendFeed’s design implied that it was actually the originating application that was most important. You could scan app icons for Twitter, or del.icio.us, or whatever, and then read title and author if the application was something interesting to you.

Old FriendFeed design, placing emphasis on icons for the originating applications.

But now FriendFeed has switched to be more Twitter-like, with author images as the key differentiating aspect of each activity bleep. The originating app is significantly downplayed.

New FriendFeed design, emphasizing author images.

What’s interesting here is that the implication is, again, I only really care about the author of the bleep, and much less than in where that bleep originated from.

Alright, back to our questions. “When scanning a stack of activity feed items, what visual cue is the user looking for to indicate that a certain feed merits more attention?” Well, in FriendFeed or any other heterogeneous activity feed, I would argue that the reader is equally interested in: author, originating application, and title of the bleep.

This would go doubly in, say, the enterprise context, where I might be much more interested in seeing all activity from, say, a wiki, and filter (in my mind) next on author or title.

Next question: “What does that imply for how activity feeds should be designed?” Well, a good design would be able to allow users to self-select what they’re scanning on, any of those three characteristics, and allow equally easy scanning, depending.

What would that look like? Well, uhhh. Here’s a quick stab at redesigning the FriendFeed stream to allow users to scan on any of those three characteristics.

Five-minute redesign of FriendFeed.

Essentially this design makes the following arguments:

• The mind will still scan primarily on author icon. The embedded originating-app icon will give a bit more context before the user scans the item title.
• If author icon and app icon were enough to pause the reader in his scan, go straight into the item title where user can get full information.
• Note that author name is significantly downplayed (in gray at bottom rather than large link in front of item title). This assumes that once you see the icon, you know who the author is, and repeating it just gets in the way of the scan.

Not sure it really works, but I do think that depending on the intent of the user, it’s difficult to say categorically that author or originating app or title is most important, so a good design should be able to communicate all three. Thoughts?

Seems like you can’t swing a dead cat around without hitting someone that’s got an activity stream built into their app, or their app is a an aggregator of activity streams. Not surprising. Twitter is enormously popular. People looove to read those tweets. This is affecting how other consumer products look at their activity UIs.

But is there, perhaps, going to be a backlash to the total information awareness wrought by having to read all these streams? Some thoughts:

Facebook rolled out its new design recently, basically making the homepage much more Twitter-like. Result: Everyone seems to hate it. I know that I personally am much more aggressively “hide”ing people in Facebook that I don’t care about (and that is, frankly, most of my connections) because I just can’t deal with all the overload.

Facebook's Twitter-like new look. I need to hide annoying people more aggressively.

Friendfeed, which is kind of an uber-aggregator of activity feeds from Facebook, Twitter, Flickr, etc. etc., has rolled out an interesting new UI at http://beta.friendfeed.com. This thing will actually show LIVE updates of your friends’ activity feeds, and, if you’ve got enough friends, will get going so fast you can’t keep up with it. They had to add a “pause” button!

FriendFeed's new Twitter-like interface. Note the "pause" button, upper-right.

Finally, consider how recently even CNN cleaned up the “UI” of their TV broadcast, removing all that constant ticker junk. They think that people are getting tired of it.

New, ticker-less CNN graphics.

Jeremiah Owyang has a quick, nice piece on how UI needs to do a better job of helping users sort the activity stream in a way that makes sense to them. Sure, definitely, but harder to do than to say. Check Jeremiah’s thoughts here.

So hey, here’s a contrarian thought: Are activity streams just another goddamn email inbox? And when they get choked with too much data, will we just stagger like zombies to some new UI/service that seems like The Solution but is actually desirable merely because it’s not clogged with crap yet?

I’m building this post as a personal cheat sheet for Data Portability efforts in social networking. Coz I can’t keep it straight. Give me a few days to construct it, at which point I’ll probably make it a separate page on this here blog.

Please let me know if you see errors, or have comments. Frankly this stuff is pretty confusing; I’m happy to have any mistakes corrected.

So, data portability in social networks is about sharing data about users (name, favorite band, who your friends are, etc.) among different Web sites and different social networks. Specifically you can think about data portability in the following ways:

• Who I Am (authentication/ID and profile info)
• Who I Know (social graph)
• What’s Going On (feeds of personal and friend activity)
• App Portability (sticking apps/widgets on other networks)

Further, it’s useful to think about those bulletpoints in terms of:

• Data In (to your own social network, say, SelectMinds corporate social networking apps)
• Data Out (to other networks, say, LinkedIn or Facebook)

Now, there are basically four horses out there. The Open Stack including OpenID, using (mostly) open standards to accomplish data portability; Google Friend Connect and OpenID which uses both the open standard OpenID and Google’s Friend Connect; Facebook Connect and the Facebook APIs, being used by Facebook and various sites that want to cash in on the Facebook mojo, and MySpace’s MySpaceID. On the outside is LinkedIn, which is keeping its user data tightly held, although it is opening up a bit.

Finally, on the enterprise side, Google and Salesforce.com are getting very cozy, while Microsoft’s Sharepoint is still in the realm of talking only to other Microsoft apps, or one-off integrations.

More on all this below…

The “Open Stack”

This mishmash of open standards is recently become somewhat subsumed by Google’s efforts with FriendConnect, but I decided to list it separately for clarity’s sake.

Who I Am

• OpenID
  -Single ID, authentication, across many sites
  -Alleged profile-attribute sharing as well
  -Used by Yahoo, Google mail, Windows Live, Plaxo, hi5, etc.

Who I Know

• Contact APIs (such as Google Friend Connect (?))
• OAuth (Share private data between trusted sites)

What’s Going On

• RSS/Atom: Syndicate your activity to share with others
• Jabber/XMPP: Real-time update stream between sites (esp. for “status”)

App Portability

• OpenSocial (Owned by Google, which is pushing it as an open standard)

Google FriendConnect mated with OpenID

Google was an early booster for open standards for data sharing across social networks (which makes sense, as it was and is lagging far behind Facebook and MySpace in terms of social network usage). To a certain extent, Google FriendConnect now mirrors the Open Stack, but I thought I’d keep ‘em separate. Details:

Who I Am

• OpenID for authentication and UserID. That’s important because of the many sites that are using OpenID for authentication. Basically, then, if your site uses OpenID, it can also leverage FriendConnect for social data and OpenSocial for widgets.
• FriendConnect for profile-attribute sharing.

Who I Know

• FriendConnect allows friend lists to be shared among any subscribing sites
• FriendConnect also supports OAuth data portability.

What’s Going On

• FriendConnect also has feed messages and other activity covered, allowing sharing of this info among subscribing sites

App Portability

• Open Social is the mechanism for placing app widgets on subscribing Web sites. Note also that Open Social gadgets can grab the social data from FriendConnect.

Facebook Connect and Facebook APIs

Facebook is the number 1 social network in the world, and fast gaining on MySpace in the US. So far, it hasn’t seemed inclined to play in the “Open” world.

Facebook allegedly has 24 launch partners for Facebook Connect, including Digg, Twitter, Plaxo, CBS. Unclear how many have actually taken it up. Here’s more on Facebook Connect.

Who I Am

• Facebook connect links Facebook profile attributes out to participating sites. Including image, and other profile attributes. Facebook connect is now open, allowing “any” third-party site that signs up to pull data about visitors from Facebook. Wow.
• Unclear if profile updates made at partner sites are pushed into Facebook.

Who I Know

• Facebook Connect enables pushing Facebook social graph information out to partner sites.
• Unclear if updates at partner sites push back to Facebook.

What’s Going On

• Facebook Connect also makes FriendFeed data available to other sites.
• And posts activity back into Facebook.

Portable Apps

• Facebook platform enables third-party developers to put their apps on Facebook, although this is an area of apparently decreasing importance for Facebook.

MySpaceID

MySpace has rolled out MySpaceID to try to catch up with Facebook. It lags behind Facebook Connect in some aspects. However, it largely embraces the Open Stack and Google Friend Connect, so could gain more leverage (read: everyone’s ganging up on Facebook). To whit:

Who I Am

• MySpaceID allows users to log into other sites using their MySpace credentials
• And allows for portability of profile attributes to other Web sites
• OpenID comptabile

Who I Know

• MySpaceID also allows for the use of social graph information on other sites

What’s Going On

• MySpaceID currently does not support publishing activity from other sites into MySpace, and publshing MySpace activity out to other sites. ETA is early 2009.
• OAuth compatible

Portable Apps

• OpenSocial

LinkedIn’s InApps

LinkedIn is only reluctantly getting into the API game, thus far only accepting a (very limited) set of third-party apps onto its site. No sharing of “Who I Am”, “Who I Know”, or “What’s Going On”. Bad LinkedIn! Thus, it’s really just:

Portable Apps

• OpenSocial-based platform. LinkedIn’s being picky about what business apps it accepts, although they’re all pretty lame so far.

Google and Salesforce.com

Comin soon….

Sources

Most of this piece is sourced from TechCrunch. Hey, they make it easy. Here are some of the articles that were helpful.

• Oh No You Don’t, Google! Facebook Connect Now Generally Available, Too (TechCrunch)
• Google Friend Connect Now Open To All Websites
• MySpace Data Availability Now Has A Catchier Name And Two New Partners
• LinkedIn Means Business With New Application Platform

I’m feeling bloody-minded and have been re-reading Don Norman’s “Design of Everyday Things.” I got on this kick because I was annoyed at Norman’s article in the latest Interactions: in discussing “social signals” (indicators of status left by human activity–for example, an empty train platform indicating you’ve missed your train) Norman has unkind words regarding “affordances”, a cherished interaction-design concept.

Affordances basically suggest how one might interact with an object. Say, the holes on scissor handles suggest your fingers go there, or the beveling of a UI button suggest that it is something to be clicked on. While psychologist James J. Gibson coined the idea in 1977, Norman borrowed the concept for “Design of Every Day Things,” cited it continuously, and basically grafted the idea into the heads of a generation of interaction designers (like me).

Now, Norman is suggesting we “forget affordances” and concentrate on social signals. Okay, Norman’s a bomb-thrower, and he probably doesn’t really mean it. There’s nothing wrong with considering a range of concepts and theories when considering how best to design a set of interactions around an object or service.

BUT: Norman’s casual murder of affordances got under my skin, and I started re-reading “Design of Everyday Things.” I’m only two chapters in, but one of the things I’m struck by, now that I’m out of grad school and less of a usability zealot, is Norman’s apparent belief that any object should be immediately understandable and usable, and, by implication, Norman’s rejection of expert utility. Secretaries should not need to be trained to use advanced phone functions; film machines should be grasped by any ol’ schmo.

I may go to user-centered design hell for it, but: I don’t agree. There is a place for experts using machines tuned to their trained and developed sensitivities. Call me elitist, but I say: YouTube’s singular impact is to prove that most people shouldn’t be allowed anywhere near a videocamera.

This all made me think of Steve Albini’s (engineer of Nirvana’s “In Utero”, dontcha know) famous mid-’90s rant “The Problem with Music.” In the midst of a wide-ranging screed against the music industry, Albini complains that untrained “crappy engineers” are recording and producing music with (then) new, easy-to-use DAT machines. saying: “Tape machines ought to be big and cumbersome and difficult to use, if only to keep the riff-raff out. DAT machines make it possible for morons to make a living and do damage to the music we all have to listen to.”

I agree. Not everything should be user-friendly.

Moderator: “Nothing says 8:30 a.m. on the last day of the conference like a math and theory-heavy session.”

Can Markets Help: Applying Market Mechanisms to Improve Synchronous Communication

CMU People. Natch.

Basic upshot: Sender does not now how costly interruption is to the receivers, and the receivers do not know how important the communication is to the sender.

Possible solutions:

• Full disclosure: disclose all information in communication. Problems: Privacy issues; people may not use the disclosed information.
• Payment markets (and the focus of this session): Can we utilize markets to improve communication efficiency, and how elaborate must hte market be to derive benefits?

So, how about if you put $5 on the value of the sent communication. Then receivers can filter out communication requests on price.

Benefits of market:

• Privacy is prserved
• Important and ugent communication wil have higher payments
• Receivers compensated for interruption.

Prior work has shown that markets can increase gains for senders and receivers. But, in real life, people aren’t very good at estimating things, estimating value.

So, they did a lab study. Participants come in and earn money by solving puzzles. they can ask for help from other participants. And communication (ask for help) is run on a no-price market, variable-price market, fixed-price market.

Results

• Market participants earneda bout a dollar more than no-market
• and the fixed-price market seemed to perform the best.
• Variable price market performed worse, but also was more prone to error and higher cognitive costs (assessing a number of prices)
• Variable price market had significantly higher time to make decision compared to fixed-price market

Interesting stuff.

Network Structure, Position, ties and ICT Use in Distributed Knowledge Intensive Work

Competing models/theories to explain technology use:

• Technology Acceptance MOdel (TAM)
• Social Influence Model
• Significance of social structural, position, and ties not well-accounted in the above models

So, what social structures affect ICT use?

Weak ties! Hearing a lot about that this conference.

And now, a completely impenetrable explanation of method. Oy, I am not smart.

Long Title: Investigating the Effcect of Dicsuiion Forum Affordances on Conversational Structures

Looking at thread structure of bulliten boards. Like, explicit or implicit threads.

Question: Is the way the discussion presented have an effect on how people internalize the discussion. (?) “Determine whtether these differences affect how people ‘talk’ “

Investigate the contribution of “Time” and “Similarity”.

Basically they’re looking at “flat” (blog-like) thread structure vs. threaded thread structure and see if that has an impact on the language that arises.

What they found: People drop cueues to other text in threaded discussions, use them heavily in non-threaded discussion. SHOCKER!

Coordinating High Interdependency Tasks in Asymmetric Distributed Teams

Petra Saskia Bayerl and Kristina Lauche, Delft University of Technology

Challenges of remote teams

• Coordination of tasks and processes
• Technology restrictions
• Process and motivation losses
• Conflicts and trust

Whoah, they looked at offshore oil production teams and the control people onshore.

Study aim: coordination for highly interpendent taks in distributed teams in foffshore oil and gas production. Implications for technology support.

Cutting Into COllaboration: Understanding Coordination in Distributed Medical Work

Collaboration is important: when it’s distributed it gets more difficult.

Loose collaboration structure can make coordination difficult.

Goals:

• understand work practices ian coordination in research
• tie practice to cscw issues sush as awareness and informal interaction

Research context:

• Hospital in big city, biomedical engineering dept in small down, 240 miles separated.

• Surgery dept: Define requirements, apply materials, conduct animal studies, analyze patient data
• BME side: develop and design materials, developm modesl, build materials and devices.

Conflicts

• Different views of time: surgeons go to OR all the time, engineers are timely and pissed off when surgeons miss meetings.
• Communication: surgeons had different views of how they should be communicated to.

Research goals conflicts

• Surgeons: clinical stuides, clear application, quick adoption
• BMG: Innovation and new materials, patents, try several attempts.

So, successful projects sometimes, how did they overcome challenges:

• Use human mediators
• Opportunistic schedule adjustment (but not always aware of remote colleagues)
• Optimize joint retreats and one-day trips

Implications for design

• Flexible calendaring
• Improved activity awareness

Future work

• what makes project succeed: how much does coordination matter, how do these strategies work longer term
• What does low-level coordination look like? Who and when do collaborators communicate? What do they share?

Summary

• Key difficulties in coordination: perceptons of hierarchy; priorities, scheduling and work locations; research goals
• Strategies to overcome: human mediators; maximizing face to face contact; opportunistic schedule adjustment and ad hoc communication

Linguistic Mimicry and Trust in Text-Based CMC

Lauren Scissors et al, Northwestern University

In face to face settings, people establish rapport through behavior mimicry, to get people to like them.

Lack this in text. Is there linguistic mimicry?

Previous research indicates that f-to-f speech patterns, people tend to adopt partner’s speach patterns.

Also, research on trust in CMC environments. Takes longer to develop trust in CMC.

Hypthoesis: Text-chat enviormenent: high levels of linguistic mimicry associated with higher level of trust, lower mimicry associated with lower level of trust. Hmmm, I’m skeptical.

Description of method…..examined mimicry: using lexical mimicry (noun or noun phrase), Text-chat abbreviation mimicry (like “u didn’t do it”), and syntactic, emotion-related character (emoticons).

Hmm, deeply skeptical of abbreviation mimicry.

WIthin-session mimicry led to higher trust. Across-session mimicry lower trust. Hm, not sure i buy it. Many approach the microphone for some of the ol’ rip-n-tear action.

Mind your Ps and Qs: The Impact of politeness and rudeness in online communities

Moira Burke and Bob Kraut, CMU

Goals

• determine impact of polite or rude language in online commnity interaction (newcomer integration, more efficient groupwork, death by monster (?))
• Build machine learning tools to automatically detect polite language
• Extend linguistic politeness theory to social interactions between strangers online

Method: survey to rate politeness of messages  in a discussion group. Code message for presence or active of specific strategies around politeness.

Linguistic politeness theory, Brown and Levinson: 15 positive strategies to increase person’s positive social value, and 10 negative strategies to decrease. Interesting, should read that sometime.

Generally, they found that rude behavior in a politics group  “helps” (that is, gets replies), where as in technical groups tend to not get responses. Well, okay. Keep in mind, that previous research points out that getting responses is what fuels future participation.

Next steps: train machine to detect language. A “Politness checker” like a grammar checker. Hm, not sure i like that. Good writing is the avoidance of cliche, not the repetition of patterns observed elsewhere.

I am waiting – Timing and responsiveness in semi-synchronous communication

Within synchronous communication, lack of responsiveness is immediately problemmatic. But what is the affect in asynchronous?

In IM, users can choose whether and when to respond to EVERY point of the conversation. And, users typically multitask n IM communications.

Objective of study: a deeper understanding of factors that affect responsiveness. They do this with a survey. Hmm. This seems kind of obvious: resposiveness is a runction of how busy i am and the perceived importance of the message. Perceived importance culd be bucketed into a few things (who sent it, subject matter, provocation, etc).

Their list:

• Identify of the buddy
• relationship with buddy
• time since liast message
• whtehr message window already existed
• whether message window was in focus

Results HIghlights and Implications

Relationship category did not have a significant impact on responsiveness. Hm, that’s surprising. But there were significant differences between individuals.

Work-fragmentation is a strong indicator of faster responsiveness

• More keyboard activity
• More mouse activity
• More app-window switches.
• Hmm, that’s interesting too.

Also: Faster responsiveness if the IM window was already open. And, signifiant efrect whether the window is covered or not. Shocker!

• Longer messages got faster responses
• Questions got faster responses
• URLs got slower responsiveness
• Emoticons marginally slower responses.

Microstructures of Social Tagging

Need to get name of presenter…University of Illinois

What are microstructures?

Relatively invariant behavioral patterns emerged from user-environment interactions.

At a functional level, cognitive processes tend to be stable across individuals.

Why do we care?

Provide explanations that cut zcross levels of activities: social levels (minutes, hours, weeks), cognitive levels (seconds, minutes), embodiment level (ms, seconds). Whoah.

Distributed congnition

Arguing that social tagging is a distributed cognitive system, where individual represntations of individual users interact with the “same” external representations of other users (tags)

Tagging is a form a knowledge exchange (your representation via a tag is interpreted by another person)

Exploratory Search

Exploratory information search characteristics

• Lack of specific information goals
• Info goals are defined throuh a series of search-and-comprehend activities
• Claim: Mental concepts are utilized (and critical) for evaluation of info content
• Okay, what does this have to do with tagging?
• Claim: social tags augment the evaluation process and thus facilitate exploratory search

How do people form and use mental categories

Peeople naturally categorize concepts. Concept formation is a rational response to information reduction.

The study (“to show you i’m not just hallucinating”)

Follow 4 users across 8 weeks. Engage in exploratory info tasks. Use del.icou.us to collect information and prepare for talk. Create tags for themselves and others.

Results

Somewhat impenetrable. Upshot seems to be arguing that tags are not just “metadata” but actually directly influence knowledge structures.

Influences on tag choices on Del.icio.us

Emilee Rader, Univ. of Michigan

Missed presenter name.

Folksonomy: Potential for the emergence of collective meaning.

Why do people choose some tags over other tags.?

Social: Tag choices influenced by the system. non-social: tag choices are idiosyncratic. Which is true?

Found: Users future tag choices are heavily influenced by tag choices they have previously made. Shocker. (and the ui specifically encourages that)

Social hypothesis: users’ tag choices are influenced by tags applied by other people.

Organizing hypothesis: users’ tag choices are personal and idiosuncratic, NOT influenced by others’ tag choices.

So we set out to look for a aconection between the small scale (individual tag choices) and the large scale (aggregate patterns). Dataset: 30 pages, hundreds of thousands of tags, thousands of users.

Final hypotheses

• Imitation: users imitate tags that previous users have used
• Organizaing: users re-use tags they ahve previously used — Our study indicates this is most imporant (But SK says: yeah, but the UI supports this one most visibly. You’re just verifying the UI effect. Right? Am I missing something? Okay, yeah, guy comes up and ask.)
• Recommended: users choose suggested tags from del.icio.us

I’m taking notes as the sessions go…

Mopping up: Modeling Wikipedia promotion decisions

Moira Burke and Robert Kraut – CMU (Bob is a failry big figure in CSCW and CHI)

How are promotion decisions made?

• Large groups of strangers colaborate to choose caretakers known as administrators
• We model successful candidates based on simple metrics that can be computed quickly in real time
• How does the community user evidence to build consensus, and are there opportunities for tools to support decision-making?

Policy capture theory:

• compare organizations stated criteria for making decisions with actual behaviors
• typically: a disconnect (now, imagine that)
• beause of:
• difficulty finding information
• cognitive overload
• weighting simple things too heavily
• process-blocking or bandwagon effects in collective process.

Method: Looked at all Admin-approvals.

• Categorized previous contributions based on RFA guide
• Modeled promotion success based on contribution history
• Several criteria listed from RFA

Hard to measure criteria:

• trustworthiness
• quality of edits

How to use: apply their model of admin-effectiveness to:

• voter dashboard or self-evaluation tool
• Admin finder bot
• Similar model for decisionmaking in other online environments like WOW

Harnessing the wisdom of crowds in Wikipedia: Quality through coordination

Aniket Kittur and Bob Kraut, CMU

Online collective intelligence:

• Predicitng
• Filtering
• Organizaing
• Recommending (netflix)

Assumptions:

• people are making independent judgements
• and you can automatically aggregate these assumptions

But that doesn’t really work for complex information processing.

Need to coordinate, collaborate. So: HOw do we harness the wisdom of crowds for complex things.  Just throwing people together won’t work. “Adding manpower to a late software project makes it: later.”

Previous research indicates that more work / more people on wikipedia leads to better articles (“Feature articles”).

Interested in coordination among authors editors:

• Explicit coordination (direct communication between authors / editors)
• Implicit coordination (structuring wrork so it is concentrated in core group; leadership role in setting scope and direction)

How to measure quality of artciles? Why, with the Wikipedia 1.0 Quality Assessment Scale!

Findings:

• Incrasing # of editors had NO INCREASE in quality
• Increasing coordination in communication and concentration resulted in higher quality.
• Communication does not scale to the crowd. High communication with few editors leads to qualtity. But scale up the editors, quality goes down.

Interesting stuff.

Articulations of WikiWork. (Good paper!)

Mass collaporations, a la wiki, are going to become more important to society.

We want to know how this work is sustained, so we studied Barnstars on wikipedia. To figure out how work is valued on wikipedia.

They review the breakdown of barnstars on wikipedia:

• Editing work: 27%
• Social and Community support actions: 25%
• Border Patrol: 11%
• Administrative Actions”: 9%
• Collaborative ations and dispositions (collaboration on pages like mediating conflicts) 8%
• Meta cntent work, the cration of tools, templates, etc. 5%
• And, undifferentiated: 14%

So note that editing only accounts for 27%. Reputation systems must award more than simple production, right?

Need reputation frameworks for complex cooperative work. Very interesting.

I spent the day yesterday in a roomful of supersmart people discussing Social Networking in the Organization. Below you’ll find a not-especially-coherent splash of notes on the whole thing. Big thanks organizers of the workshop, who made it an interesting day and patiently tolerated my industry-skewed blathering.

• Joan DiMicco – IBM Research
• David Millen – IBM Research
• Jonathan Grudin – Microsoft Research

Some Key Themes Discussed / Questions Raised

Going from memory here…

• Goals and needs that populations tend to bring to social networking software. What are they?
• Jonathan Grudin talked about the classic CSCW paper from McGrath which plots the work that goes on in groups and teams on an axis. (Haven’t read this paper…need to.) Usually people pay attention to the production portion of that plotting, but perhaps with social software we should be looking a lot more at how SNS affects the team building and member support activities of team work. Interesting.
• Great deal of discussion on how to measure activity and assign it a value of SNS. I’d been jabbering a lot, so I did not bring up Rob Cross’s Social Network Analysis work, but Cross has an interesting angle on it.
• Design for sales. I mentioned that occasionally we’ve built features that our clients sometimes don’t actually use, but which must be there in order to make the sale. Millen mentioned there might be a paper in there somewhere.
• What constitutes “inappropriate” content…the kind of content that an enterprise theoretically would want to control. Profanity? Sure. Thoughtful criticism of the sponsoring company’s strategic goals? Perhaps. A survey study of different organizations to find out just what constitutes “inappropriate” would be pretty interesting.
• Plenty more…but space / attention is limited…

Finally, I railroaded a good part of the final discussion into consideration of how moderational / monitoring controls impact population activity / contributions. Patricia Romeo from Deloitte, who has led the development of their internal social networking app, was astonished at how much monitoring / moderational control is built into the SelectMinds application (and if Patricia was astonished, the IBM people were aghast…apparently anything goes on their internal SNS).

Fair enough. There’s no doubt that more moderational / monitoring intervention = less activity, less robust network. My challenge was: can we actually study and quantify the impact of different moderational / monitoring approaches to robustness of the community? That would allow me to present clients with a cost-benefit framework around moderational control. Maybe that’s my next paper.

Some interesting topic that came up, and links

Dana Boyd – PhD researcher concentrating on “faceted identity” online. Related to my last few blog posts, will need the check these out.

HCI Remixed – Includes Grudin’s essay on McGrath’s older paper. Will need to buy this.