I played a bit with the Twitter for iPad app (announced recently on the Twitter blog), and found it a pleasant experience for casual use, but not particularly well-suited for more intensive use that involves multi-tasking. The slide-over pane organization is elegant and more usable than TweetDeck for iPad’s browser. It works particularly well for reading web pages in portrait mode: pages can be zoomed to hide the ads and show just the main column in a reasonably-sized font.
Blog Archive: 2010
Early last year, Daniel Tunkelang proposed a way to measure people’s influence on Twitter; this metric was dubbed TunkRank, and Jason Adams put up an implementation of it that people could use to calculate their (and others’) scores. The site has been evolving, and getting slicker. It even has an API for incorporating these scores into other applications.
The basic premise of the algorithm is that its not how many followers you have, but how influential they are. Your influence flows from them. For those interested in more details and rationale about algorithm, Daniel’s slides from a recent talk offer a nice overview. What’s also interesting, as pointed out in the comments on his post, is that this model, proposed on the blog and never published in a peer-reviewed forum, has become quite influential.
There are lots of ways to display search results, and the familiar (if impoverished) ranked list of links with snippets is just one possibility. It doesn’t work particularly well for Twitter, for example because for many kinds of searches it’s hard to make sense of the tweets individually; instead, a more holistic approach is more appropriate. I described in one such approach in Making Sense of Twitter Search (the position paper was co-authored with Miles Efron and was presented at a CHI 2010 workshop on microblogging) .
Paper.li is another approach to visualizing sets of Tweets. For a given topic or user, it identifies documents referred to by your followers and builds a two-column online newspaper-style layout out of those documents. It classifies documents by broad categories (media, education, technology, etc.) and prominent hashtags (e.g., #facebook), show the leading paragraphs or two of the document, and the person who tweeted it. Media such as YouTube videos are embedded directly into the layout. And, you can, of course, switch to a list view.
It seems that the Twitter API function that returns @mentions fails to return new-style retweets. I discovered this by accident after seeing references to tweets on my blog that TweetDeck didn’t show me in the @mentions column. I then looked on the Twitter site, and saw the same behavior there.
This seems like yet another problem with the RT API, and, like the lack of ability to add comments to a new style retweet, this behavior also seems unwarranted. It doesn’t really complicate the system to include new-style RTs of one’s tweets in @mentions, and it certainly makes for a more consistent interface.
If Twitter doesn’t fix it API, perhaps the good folks at TweetDeck could inject those missing tweets into the @mentions stream.
The use of Twitter at conferences seems to be growing, and I think we are beginning to see some limitations of the current tool suite with respect to making use of tweets at a conference in real time. At CHI 2010 I was not able to participate much in live-tweeting because I did not want to carry my heavy Thinkpad T61 around all day, and my iPhone wasn’t up to the task. While the iPhone was adequate for checking e-mail and using the CHI 2010 schedule app, the battery would run down by the end of the day of intermittent use. Furthermore, the screen wasn’t large enough to take notes, type tweets in a timely manner, and to keep up with the stream of tweets from other attendees. In fact, in some cases it seemed that people who were following the conference remotely had a better grasp of the breadth of activity in the sessions than I did at the conference.
Yesterday Miles Efron and I presented our work on Twitter search at the CHI 2010 microblogging workshop.We distinguished between macro- and micro-level research on Twitter, and then focused on Twitter search from the end-user’s perspective. We talked about the role that test collections should play in evaluation of search interfaces. The slides are shown below.
Twitter is a trending topic in HCI research these days. The ICWSM conference is awash with interesting papers on mining and analyzing the Twitter stream, and the upcoming CHI 2010 microblogging workshop promises to be full of interesting discussion on a range of topics around how people use Twitter to communicate.
One of the established ways of studying Twitter use is to collect samples of tweets (e.g., see here) to perform statistical and social network analysis to understand the patterns latent in the tweets. This makes for interesting and (furthermore) publishable research.
On the other hand, the focus on large datasets and aggregate behavior forgets about individual. Not about the individual as a person who contributes tweets to the larger collection, but about the individual who needs to use Twitter to meet his or her information needs.
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.
I’ve been using TweetDeck for over a year now, both on my laptop and on my iPhone. It’s a great tool for managing a moderate stream of tweets. The columns offer a convenient way to segment and organize tweets, and its display of certain media in-line is convenient. In the spirit of constructive criticism, I would like to offer a set of suggestions (some obvious, some maybe not) on how its user experience might be improved.