Figure 1: The fluctuations in volume of Twitter messages sent during U.S. President Barack Obama’s inauguration show moments in time when users paid more attention to the ceremony (drop in volume) than to their computer use.

topic boundaries with about 92 percent accuracy [ 2]. All this is done without looking at any text.

The question then became, “Can this method of ‘naïve tweet counting’ scale?”

twitter’s explosion

Twitter has grown at an incredibly fast rate. In January of 2009, CNN Breaking Ne ws had around 86,000 follo wers. Nine months later, its follower count had exceeded 2. 7 million. T witter began offering data-mining push feeds that hands back 600 tweets a minute. Track feeds push all the tweets related to a search, and Twitter’s “Firehose” can deliver everything if you can get your hands on it. I previously sampled 3,000 tweets from a 90-minute debate. I saw 52,000 tweets from a 90-minute sample of President Obama’s inauguration speech.

Addressing scale, I revisited the
human-centered observation I origi-
nally questioned at Dolores Park. If we
position people tweeting while watch-
ing a live event, either in person or on
television, conversation is represented
as talking to someone else: in effect
directing a tweet with the symbol
(using “@” before a username like @ba-
rackobama pushes a highlighted tweet
into that person’s feed). The highlight-
ed tweet becomes more visible; it calls
attention to the user, like tapping your
friend on the shoulder in a crowd.

utes into 5-minute chunks, then find a highly salient slice term that is not salient in the other chunks. Looking back at the inauguration, this produces topic segments like: booing, Aretha, Yo-Yo Ma, anthem, and so on. Couple these words with our importance proxy, and we find the illuminating moments of Aretha Franklin’s performance, Obama’s speech, and the nation anthem to have greater importance than the other moments.

The signal of human activity here is clean and simple. Our analysis was done on a MacBook Pro using R and MatLab, without the need for large-scale assistance from a Hadoop cloud or Mechanical Turk.

Tweets can be used in social-multi-media research, when facilitated through human-centered research, to identify the shape of the related event. More than just text alone, the form of the conversational shadow has to account for the structure of tweets themselves. Hashtags, mentions, and other communication mechanism, both structured and ad-hoc, follow but likely do not mirror the visual content of the event itself. This link between two disparate data streams (online conversations and live events) provides rich opportunities for further investigation.

As we explore new approaches to better navigate, communicate, visualize, and consume events, our tools and research should firmly be based in the conversation structure, be it Twitter, Facebook, or Flickr, and be motivated by our interactions in everyday life, less we miss the game in the park.

 

Biography

David Ayman Shamma is a research scientist in the Internet Experiences group at Yahoo! Research. He researches synchronous environments and connected experiences both online and in the world. He designs and prototypes systems for multimedia-mediated communication, and develops targeted methods and metrics for understanding how people communicate online in small environments and at web scale. Ayman is the creator and lead investigator on the Yahoo! Zync project.

 

a taBle oF contents Finally, when we turn to examining the text itself, a table of contents emerges. For this pick your favorite off-the-shelf information retrieval tool; mine is TF/ IDF. What we want is a very specific table of contents, so we split the 90-min-

References

1. Cesar, P., Geerts, D., and Chorianopoulos, K. Social Interactive Television: Immersive Shared Experiences and Perspectives. Information Science Reference, 2009.

2. Shamma, D. A., Kennedy, L., and Churchill, E. F. Tweet the debates: Understanding community annotation of uncollected sources. In WSM ’09: Proceedings ofthe international workshop on Workshop on Social Media (Beijing, China, 2009), ACM.