Given the extraordinary ascent of all things social in today’s online world, we could hardly neglect this theme at the CIKM 2011 Industry Event. We were lucky to have Ed Chi, who recently left the PARC Augmented Social Cognition Group to work on Google+, presenting “Model-Driven Research in Social Computing“.
Ed warned us at the beginning of the talk that his focus would be on work he’d done prior to joining Google. Nonetheless, he offered an interesting collection of public statistics about social activity associated with Google properties: 360M words per day being published on Blogger, 150 years of YouTube video being watched everyday on Facebook, and 40M+ people using Google+. Regardless of how Google has fared in the competition for social networking mindshare, Google is clearly no stranger to online social behavior.
Ed then dove into recent research that he and colleagues have done on Twitter activity. Since all of the papers he discussed are available online, I will only touch on highlights. I encourage you to read the full papers:
- Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network
- Tweets from Justin Bieber’s Heart: the Dynamics of the “Location” Field in User Profiles
- Is Twitter a Good Place for Asking Questions? A Characterization Study
- Language Matters in Twitter: A Large Scale Study
- Eddi: Interactive Topic-based Browsing of Social Status Streams
- Short and Tweet: Experiments on Recommending Content from Information Streams
- Speak Little and Well: Recommending Conversations in Online Social Streams
Ed talked at some length about language-dependent behavior on Twitter. For example, tweets in French are more likely to contain URLs than those in English, while tweets in Japanese are less likely (perhaps because the language is more compact relative to Twitter’s 140-character limit?). Tweets in Korean are far more likely to be conversational (i.e., explicitly mentioning or replying to other users) than those in English. These differences remind us to be cautious in generalizing our understanding of online social behavior from the behavior of English-speaking users. Ed also talked about cross-language “brokers” who tweet in multiple languages: he sees these as indicating connection strength between languages, as well as giving us insight to improve cross-language communication.
Ed then talked about ways to reduce information overload in social streams. These included Eddi, a tool for summarizing social streams, and zerozero88, a closed experiment to produce a personal newspaper from a tweet stream. In analyzing the results of the zerozero88 experiment, Ed and his colleagues found that the most successful recommendation strategy combined users’ self-voting with social voting by their friends of friends. They also found that users wanted both relevance and serendipity — a challenge since the two criteria often compete with one another.
Ed concluded by offering the following design rule: since interaction costs determine number of the people who participate in social activity, get more people into the system by reducing interaction cost. He asserted that this is a key design principle for Google+.
My skepticism about Google’s social efforts is a matter of public record (cf. Social Utility, +/- 25%; Google±?). But hiring Ed Chi was a real coup for Google, and I’m optimistic about what he’ll bring to the Google+ effort.