This may be old news to some of the true social media junkies, but thanks to Gentry Underwood’s PARC forum today, I saw a great video analogy for the Facebook interaction style. Enjoy.
The video is made by a British comedy group called Idiots of Ants; the pun becomes evident when the group’s name is pronounced with a British accent.
In the aftermath of the recent SXSW event, Alexandra Samuel wrote on the HBR blog about five unsolved problems facing Social Media. She enumerated contact list overload, search overload, information overload, brand overload, and apathy overload. It’s not clear to me, however, whether these are pressing issues, and whether universal solutions to them would constitute an improvement over the current chaos.
(Please be aware that some ChatRoulette links may contain mature content.)
Dear me. All those folks doing naughty things on ChatRoulette, secure in their Net-anonymity, may suddenly meet a rude awakening: Chat Roulette Map, a new Google Maps mash-up, maps users’ chat image to their location, based on IP address. Last week, it also showed users’ ip addresses.
Note that Chat Roulette Map has just added a new pop-up window when you first load the page:
Welcome To Chat Roulette Map
(snip)
We’d like to advise maine.edu to stop using
student’s names in their hostnames.We’ve decided, at least for the time being, to
hide IP & host information as some user-identifiable
information was found in some entries.
No, you think? It’ll be interesting to see how this warning window evolves over the next few weeks.
Michael Bernstein and the usual suspects wrote a nice position paper for the CHI2010 microblogging workshop. They describe Eddi, a system that allows people to group tweets by topic to make sense of large numbers of tweets. In some sense, they are addressing a similar problem to the one that Miles Efron and I tackled in our paper. In both cases, the system uses various sorts of analysis to group and filter tweets to help people understand the collection or the stream.
Kate Ehrlich and N. Sadat Shami have written a paper (accepted to ICWSM 2010) that compares IBMers’ use of Twitter and an internal micro-blogging tool (with the unfortunate title of BlueTwit). The paper analyzes tweeting patterns of 34 people over a four month period. The authors found that people in their sample tended to use both system more for question asking/answering and dissemination of information than for status updates, which contrasts with Namaan et al.’s finding that “meformers” (i.e., people who tweet about what they are up to) out-number “informers” in the sample they analyzed.
Ehrlich and Shami’s study found that people used these tools to improve the social status: internally to manage their reputation, to be seen as a source of useful answers rather than just of questions, and on Twitter both to promote their company and to develop their professional status.
Marti Hearst gave an interesting talk at JHU on Social Media in which she described some important dimensions of through which we can understand the variety of phenomena that are tagged with that label. She examined expertise, the degree to which data are shared (synchronized!) among the people engaged in some activity, and the degree to which participants are working toward an explicitly-shared goal (even if they approach it different personal motivation).
Yesterday Yahoo! announced that it reached an agreement with Twitter to incorporate the twitter feed into its properties in a variety of ways, including surfacing tweets related to particular topics, return more tweets in search results, and allow users to read their tweets and tweet directly from their Yahoo! pages. The move is interesting more as another vote for the importance of Twitter as a communication channel than in the value it introduces into people’s interactions with Yahoo!
Hillary Mason of bit.ly wrote a nice summary of some key issues raised in the recent Search in Social Media 2010 workshop. (For other commentary, see Daniel Tunkelang’’s post and our pre-workshop comments.) Hillary asked several important questions, that break out into two main topics: what and how can we compute from social data on one hand, and what are the implications of those computations. Aspects such as computing relevance, how to architect social search engines, and how to represent users’ information needs in appropriate ways all represent the what and how category. We can be sure that adequate engineering solutions will be found these problems.
The second topic, however, is more problematic because it deals more with the impact that technology has on the individual and on society, rather than about technology per se.
Last Wednesday Jeremy and I participated in the SSM2010 workshop organized by Ian Soboroff (NIST), Eugene Agichtein (Emory University), Daniel Tunkelang (Google), and Marti Hearst (University of California, Berkeley). It was a full day of panels, discussions and poster presentations on a variety of topics related to search, to social media, and how to combine the two. In an earlier post, I wrote about one way that we can characterize the space, and Daniel did an excellent job of summarizing the workshop, which was also cross-posted at BLOG@CACM.
I am still trying to digest all that I learned during the day, but I can say that one of the challenges was live-tweeting the event. I was one of several people who tweeted about what was happening in the panels and about the issues that were raised. Over 500 tweets were sent and resent with the workshop’s hashtag by people at the event and elsewhere. It was interesting to see other people pick up some of the topics and comment on them. In particular, several of my twitter friends who are not part of the SSM research community had commented on the tweets, and retweeted certain aspects of the discussion.
Jeremy and I have been busy preparing for the Search in Social Media (SSM2010) workshop. We thought we would start at the beginning and ask what people understood by the term “search in social media.” Workshops often spend a bunch of time on definitions, and we thought we’d jump in early. We’ve talked about social search before, but that was without reference to social media.
We think the phrase ’search in social media’ has been used to refer to both the information being searched, and to the process for doing so. The information is standard user-generated content — tweets, blog posts, comment threads, tags, etc. The process, however, seems less well understood.