Agents of Diffusion – Insights from a Survey of Facebook Users, Rebecca Ermecke, Philip Mayrhofer, Stefan Wagner

On viral adoption on Facebook

Beyond Microblogging: Conversation and Collaboration via Twitter, Courtenay Honeycutt, Susan C. Herring

How people use the @ reply mechanism in Twitter. Did you know that 30% of messages get replies?

A Conceptual and Operational Definition of ‘Social Role’ in Online Community, Eric Gleave, Howard T. Welser, Thomas M. Lento, Marc A. Smith

A theoretical paper on determing social roles in an online community. Best paper award for the Track.

Hello Stranger! A Study of Introductory Communication Structure and Social Match Success, Daphne R. Raban, Stephen T. Ricken, Sukeshini A., Grandhi, Nathaniel Laws, and Quentin Jones

Social introductions.

Mycrocosm: Visual Microblogging, Yannick Assogba, Judith Donath

Overview of the mycrocosm service.

Cyber Migration: An Empirical Investigation on Factors that Affect Users’ Switch Intentions in Social Networking Sites, Cheng Zengyan, Yang Yinping, John Lim

What triggers migration between different social network sites?

A Life Cycle Model of Virtual Communities, Elham Mousavidin, Lakshmi Goel

The lifecycle and stages of an online community

Knowledge Workers and the Realm of Social Tagging, Ralph Boeije, Gwendolyn L. Kolfschoten, Pieter de Vries, Wim Veen

Social tagging by workers.

Groupware for Design: an Interactive System to Facilitate Creative Processes in Team Design Work, Arjun Venkataswamy, Rajinder Sodhi, Yerkin Abdildin, Brian P. Bailey

How do you design groupware that is specifically supposed to support the creative process of team design work?

Cultural Diversity, Perception of Work Atmosphere, and Task Conflict in Collaboration Technology Supported Global Virtual Teams: Findings from a Laboratory Experiment, Souren Paul, Sumati Ray

I already blogged about this one and how it is an interesting finding about conflict and cultural differences in distributed teams.

Blogs Are Echo Chambers: Blogs Are Echo Chambers, Eric Gilbert, Tony Bergstrom and Karrie Karahalios

Are bloggers talking to like-minded bloggers?

Employee Adoption of Corporate Blogs: A Quantitative Analysis, Sunil Wattal, Pradeep Racherla, Munir Mandviwalla

Model of when/why employees start blogging.

Monetizing the Internet: Surely There Must be Something other than Advertising, Eric K. Clemons

Great title and interesting discussion of some other possibilities for making money on the internet, besides through advertising.

Mycrocosm is a mix of many eyes light-weight visualizations and twitter light-weight sharing. It was so easy to make the graph that I’m tempted to start using this for different things. I need to start looking for personal data to collect and share. In some ways, this is similar to Slifeshare, a retired feature in Slife.

Babble is similar to a multi-channel textual chat system except that its conversation persists over sessions, allowing both synchronous and asynchronous talk. Its aim is to support everyday, opportunistic interaction among members of a workgroup. [link]

I never used Babble (it was built in 1997 and used internally at IBM before I joined), but it is one of the projects that inspired my thesis research. Its key concept is social translucence:

Social translucence is the idea that we should make some (but not all) cues about the presence and activity of users of digital systems available to one another. [link]

Twitter fits this criteria and has a lot of the same features as Babble:

• you can communicate either synchronously or asynchronously (txt, mobile, browser, etc… )
• you can see who is present (Twitter’s following and followers pictures)
• you can see who is active (Twitter’s time-sorted list of who said what)
• you can selectively determine who sees your posts (direct messages, @ messages, broadcast)

The main differences between Twitter and Babble are:

• Babble has a graphical visualization showing who is currently engaged in the conversation
• Twitter’s “groups” are not bounded. Even though you and I might be following each other, my group is probably different than your group. It is possible there could be 0% overlap, but we could still communicate.
• The cultural norms of Twitter are pretty distinctive in that people use “tweets” to give casual updates on their latest thoughts, ideas, opinions and experiences. The updates are not solely focused on workgroup interaction, like Babble was conceptualized to be for. But I see this as Twitter’s unusual strength.

It would be great if Twitter had some social visualization capability. (Maybe it does? Anyone know?) Then it really would be Babble, adapted for the flexible, ad-hoc type of collaboration and communication we do in this post-2000 world.

If you haven’t read them already, I highly recommend these papers on Babble and social translucence:

Socially Translucent Systems: Social Proxies, Persistent Conversation, and the Design of “Babble”, by Thomas Erickson, David N. Smith, Wendy A. Kellogg, Mark Laff, John T. Richards, Erin Bradner. In Human Factors in Computing Systems: The Proceedings of CHI ‘99. ACM Press, 1999.

Social Translucence: An Approach to Designing Systems that Support Social Processes by Thomas Erickson and Wendy A. Kellogg. In Transactions on Computer-Human Interaction. Vol. 7, No. 1, pp 59-83. New York: ACM Press, 2000.

As you watch the debates, even though CNN has told you that these uncommitted Ohioans are not a statistically representative sample, you are influenced by their knob turning. Just like you can be influenced by your friends’ laughter and comments in a face-to-face group setting, as you watch those lines moving up and down, you are convinced that McCain is angry and Obama is presidential. There is lots of experimental evidence of this from previous elections (read the OTM transcript).

My PhD thesis focused on this exact issue: real-time visualizations of social behavior and how this information changes the dynamics and your perceptions of an interaction. For my project, Second Messenger, I focused on small, face-to-face groups receiving feedback about their group dynamics, but the phenomenon is universal and extends beyond social visualization. Behavioral economists refer to it as framing.

Besides being interesting to think about, it is important to consider the influence of the squiggly lines. First, CNN should be aware of its power to influence viewers. Second, viewers should be aware that their attitudes can be manipulated by this relatively simple and unrepresentative data point. They discussed this a bit on OTM:

BOB GARFIELD (interviewer): We have established that the squiggly lines do not represent any statistically significant data. And … we’ve established that people are influenced by the squiggly lines. Does that not mean that it is journalistically irresponsible to put them on the TV? I mean, is CNN doing the right thing in adding this feature to its coverage?

SAM SCHECHNER: We’re social animals. We process information in the context of the people around us. We do watch our debates with friends or at a bar or in some sort of group environment, frequently, in part because we want to hear the reactions of other people. That’s in part why … you and I can’t stop looking at that CNN line on the bottom of the screen.

I think it’s hard to argue, necessarily, that it’s a bad thing. In fact, the people who do it – the professors at SMU – see it as a way of shifting some of the balance of influence from pundits, who have been shown to be able to have a pretty strong effect with their pre- and post-debate spin and how they set expectations and frame the debates to actual voters.

I’m not sure I agree that uncommitted Ohio voters are the antidote to polarizing pundits, but something to think about.

More information on the report:

WSJ, 10/10/08: “When Your Political Opinion Isn’t Yours Alone” Broadcasts of Political Debates That Include Live Audience Feedback Can Influence What You’re Thinking

More on my research:

Joan Morris DiMicco, Kate J Hollenbach, Anna Pandolfo, Walter Bender. (2007) “The Impact of Increased Awareness while Face-to-Face.” Special Issue on Awareness Systems Design, Human-Computer Interaction. Volume 22 (2007), Number 1.

Wordle was created by Jonathan Feinberg, another member of IBM Research’s Collaborative User Experience group.

One week before the 2004 presidential election, participants completed a survey of their attitudes concerning George Bush and John Kerry while viewing photographs of both candidates side by side (See Figure 1). For a random one-third of the subjects, their own faces were morphed with Kerry while unfamiliar faces were morphed with Bush. For a different one-third, their own faces were morphed with Bush while unfamiliar faces were morphed with Kerry. The remaining one-third of the sample viewed un-morphed pictures of the candidates.

Post-experiment interviews demonstrated that not a single person detected that his or her image had been morphed into the photograph of the candidate. Participants were more likely to vote for the candidate morphed with their own face than the candidate morphed with an unfamiliar face. The effects of facial identity capture on candidate support were concentrated among weak partisans and independents; for ‘card carrying’ members of the Democratic and Republican parties, the manipulation made little difference. [more]

We have more affinity for people we perceive to be more like us and subtle changes to a person’s picture have the power to make us like someone more or less. So be a critical consumer of not just the words but also the images of the candidates! Resist the temptation to vote based on gut feelings about affinity and similarity, because these factors can be easily manipulated.

1. The HCI field (and the CHI conference) began in the 1980’s with a strong grounding in computer science and cognitive science. Card, Newell, and Moran’s The Psychology of Human-Computer Interaction is considered the seminal textbook describing this approach.
2. Computer science and cognitive science guide us towards taking a systematic, scientific approach to building and evaluating software (for e.g. GOMS). This is a solid way to build systems and many of the early successful HCI research projects utilized this approach.
3. As the software and consumer electronics industries exploded over the last two decades, it has become obvious that there is something more going on here driving user adoption, in addition to computer science innovation and cognitive science usability. You could summarize this as “design” or “context” or “the third paradigm.” However you describe it, it has to do with human emotions, social dynamics and desire.
4. As Greenberg pointed out in his paper presentation, evaluating an early prototype in a systematic way, particularly in terms of usability, can kill the innovation process. Early design often gets things wrong, but it is a critical stage in the product innovation cycle and should not be stunted through rigorous evaluation. He claims that inappropriate evaluation is harming the quality of the work presented at CHI — read Greenberg and Buxton’s paper for more details.
5. The CHI community is struggling to find an identity that simultaneously supports a scientific process (so that there is a criteria for judging quality) and product innovation (so that CHI has an influence over the technology world, outside of academics).
6. The paper The Three Paradigms of HCI (Harrison, S. Tatar, D. and Sengers, P.) tries to define exactly what this “third” thing is that is missing from our traditional HCI education, calling it the “phenomenological matrix.” Research practices this third paradigm include are ethnography, action research, practice-based research, and interaction analysis, where the “goal is to grapple with the full complexity around the system.”
7. Because I’ve been working within the space of design, social psychology, and “context” for so long, this approach to building technology seems so logical, yet surprisingly hard to justify to CHI paper reviewers. But on the other hand, my response should not be to reject the CHI’s body of work as misguided or uninformed. I think a rejection of stringent evaluation techniques should not lead to a rejection of the innovations that have been born out of this structure.
8. My conclusion from this is that I should read more, spending time becoming more aware of and inspired by the work done before us. I’m all in favor of coming up with alternative evaluation methods or no evaluation criteria so that we can foster risky, exciting ideas within HCI. But I don’t want to abandon all the early work’s ideas.

Some Recommended Readings:


The Psychology of Human-Computer Interaction, Stuart K. Card, Thomas P. Moran, Allen Newell

Twenty-five years ago, Card, Moran and Newell’s book, “The Psychology of Human-Computer Interaction”, named our field and launched us into a new world of user-centered design and development. These pioneers believed that “a scientific psychology should help us in arranging [the human-computer] interface so it is easy, efficient, error-free – even enjoyable.”

Saul Greenberg & Bill Buxton’s paper “Usability Evaluation Considered Harmful (Some of the Time).“

Current practice in Human Computer Interaction as encouraged by educational institutes, academic review processes, and institutions with usability groups advocate usability evaluation as a critical part of every design process. This is for good reason: usability evaluation has a significant role to play when conditions warrant it. Yet evaluation can be ineffective and even harmful if naively done ‘by rule’ rather than ‘by thought’. If done during early stage design, it can mute creative ideas that do not conform to current interface norms. If done to test radical innovations, the many interface issues that would likely arise from an immature technology can quash what could have been an inspired vision. If done to validate an academic prototype, it may incorrectly suggest a design’s scientific worthiness rather than offer a meaningful critique of how it would be adopted and used in everyday practice. If done without regard to how cultures adopt technology over time, then today’s reluctant reactions by users will forestall tomorrow’s eager acceptance. The choice of evaluation methodology – if any – must arise from and be appropriate for the actual problem or research question under consideration.

The Three Paradigms of HCI, S Harrison, D Tatar, P Sengers

Informal histories of HCI commonly document two major intellectual waves that have formed the field: the first orienting from engineering/human factors with its focus on optimizing man-machine fit, and the second stemming from cognitive science, with an increased emphasis on theory and on what is happening not only in the computer but, simultaneously, in the human mind. In this paper, we document underlying forces that constitute a third wave in HCI and suggest systemic consequences for the CHI community. We provisionally name this the ‘phenomenological matrix’. In the course of creating technologies such as ubiquitous computing, visualization, affective and educational technology, a variety of approaches are addressing issues that are bad fits to prior paradigms, ranging from embodiment to situated meaning to values and social issues. We demonstrate the underlying unity of these approaches, and document how they suggest the centrality of currently marginal criteria for design, evaluation, appreciation, and developmental methodology in CHI work.

Thomas Erickson, David W. McDonald’s new book, HCI Remixed: Reflections on Works That Have Influenced the HCI Community

From Tom Erickson’s web page:

The goal of the HCI Remixed project is to produce a collection of essays in which researchers and practitioners reflect on a paper or other piece of work by someone else, that is at least 10 years old, and that has had a personal impact on their view of or approach to HCI.

It is that type of day where you mean to get some work done, but you first have to check out your blogs. Because checking blogs is kind of like getting work done, right? So of course I’ve spent half of Saturday catching up on politics and pop culture and not getting any work done. Unintentionally though I think I found something to help with my data analysis, which I swear I will get down to as soon as I finish this blog post!

On Lynn Cherny’s blog post about Colbert and book sales, I was admiring the data charts she posted from Juice Analytics. Turns out they have a bunch of tools and tips for making your chart-junky Excel charts look a wee bit better with a simple click of the button. I’ve downloaded their CleanCharts Excel Add-on and, when it works (kind of quirky), it works great. I also picked out the best of the charts in their Chart Chooser and downloaded those templates.

And I need a place to save this, so why not use the blog?

Joan DiMicco, Nicole Yankelovich. (2007) “Constellation: Using Visualization to Find the Path to Experts.” Poster Presentation at the ACM Conference on Organizational Computing and Goupware Technologies (GROUP 2007), Nov 2007.

This image is a screenshot of Constellation. The nodes are people and the lines are the relationships. The social network relationships shown are the management structure, co-authoring history of internal and external documents, patenting history, and neighboring offices. The blue lines (the thicker lines) represent multi-dimensional relationships, meaning the pair are connected in multiple ways, such as both authoring and patenting together. The user can turn any of these relationships on/off at will.

What I think is cool about Constellation is that you can figure out the relationships between experts in a topic area, for example here the experts in “hardware” are shown in the screenshot. There are two hardware research clusters in Sun Labs that have done a lot of work together, but haven’t done any collaboration across each other. The weak linkages between these two clusters of researchers is a tie that says “sits near.” So if you wanted to begin to have these groups work together (by writing papers or patents together), the first step is to go to the people who have the “sits near” relationship and get them to start talking to each other.

The proposed use of Constellation is for novices. If I add myself (a novice in “hardware”) to the graph, I can see the shortest relationship path between myself and the experts already shown. By exploring the relationships between these experts and myself, I can figure out the best way to get a personal introduction to an expert in hardware.

Users have so much knowledge about who they know and who they comfortable asking for help from that is NOT captured electronically, that I think the strength of Constellation is leaving the ultimate decision of who to contact entirely up to the user. Rather than presenting the user with a ranked list of mysteriously calculated “hardware experts,” this interface lets the user visually explore the social network space and selectively focus in on the persons of interest.

(I also wrote about an extension of this project for the CHI 2007 Shared Encounters Workshop, “Enriching Encounters with Social Networks.“)

Here’s a mash-up of Google Maps with the ubiquitous Yet Another Social Networking Service (YASNS), Facebook.com:

MapYourBuddies!

Where did your friends grow up?

(Found on Google Maps Mania.)

Clusty generates a tag cloud for you from any search term. It seems pretty interesting. I found this through Ghostweather.

It is interesting to see what it comes up with from a search on my name — most prominent are my graduate school advisors who have been my most frequent co-authors. I’m impressed it got my current and past employers, but I wish it would drop the proper names entirely and show more descriptive keywords. But anyway, kind of a fun little widget to put out there.

If you are on a Mac, there’s a new application you can use to track what you do on your machine throughout the day. Maybe it can help you get a better answer to the eternal question “where does the time go?” It can definitely show you some interesting visualizations of how and when you use different applications on your machine.

The tool is called Slife, from Slife Labs. From the website:

Slife is a new application for the Max OS X that lets you visualize and organize your computer activities like never before. Slife observes your every interaction with applications such as Safari, Mail and iChat and keeps tracks of all web pages you visit, emails you read, documents you write and much more.

From what I keep reading and seeing from the “MySpace” generation, there is a strong desire to share status with friends, family, and even loose contacts. And Slife Labs has an add-on tool to allow you to share your Slife captured actions and publish them to your contacts. So if you want to share more information with your friends about how you are spending your time, SlifeShare offers you a new way to do that:

A Slifeshare is an online space where you share your digital life activities such as browsing the web and listening to music with your friends, family or anyone you care about.

It is all very interesting stuff and reflects the current trend of capturing and sharing life data.

If you don’t work at IBM, you probably are not aware that this week is Lotusphere.
As an IBM and Lotus Notes newbie, I’m only just beginning to understand the history and culture surrounding the IBM Lotus products. Basically, Lotusphere is like Macworld for Notes users, although admittedly not quite as cool. (Sorry, no iPhone, but we got SameTime 7.5.1!) Because the Lotus software products are focused around collaboration and workplace productivity, these products are the ones most closely related to my research and the research of the other members of the Collaborative User Experience group.

This year’s Lotusphere has generated a lot of press (I don’t think this is usual), but it is fun to see press about the research projects of my colleagues.

InformationWeek has an nice article covering the coolest research that will hopefully become Lotus products:

One of the best things about the IBM Lotusphere conference is always the glimpses it gives you of the future of computing. The various IBM Research labs send representatives who staff a room filled with demo pedestals — two dozen this year — where creators show off their projects. This year, as usual, several projects look like good prospects to become future products, and IBM Lotus has even put one up on the Web so you can get a look at it even though you’re not at the conference.

The article mentions Malibu, Tagging in software development, and Many Eyes, all from CUE.