The new social face of multimedia tagging.

I’ve never been too concerned with definitions—early in my graduate career I realized they were more often used for turf wars. Just as George Carlin fought to get a definition of what he could or couldn’t say, he showed us a description can be way more powerful. Lately, I’ve been describing quite a few things around people tweeting while watching TV or when at a concert. Currently, there are several great studies characterizing Twitter users. Less concerned with this, I was wondering, “if everyone watching the superbowl tweets what they think about whats happening, what does that say about the sporting event itself” (from a classic Multimedia perspective).

Using a sample of tweets captured from the first presidential debate, I began to investigate if conversationally, people behave the same way as they do when they watch TV. It turns out they do; my colleagues (Lyndon and Elizabeth) and myself were able to topically segment the the first presidential debate and identify the main people in the video, all by looking at a collection of tweets captured from the 90 minutes of the debate.

There are many gritty details (including the usage of Newton’s Method and Eigenvector Centrality) in the full paper to be presented at ACM MM’s first workshop on Social Media. Aside from methodology, we are suggesting there is more to media annotation than explicit tags on Facebook or Youtube. In fact, if Naaman tweets “I miss Paula #idol” while watching American Idol, he is leaving a comment/annotation on the media…despite there being no proper URI where Idol exists (yet!).

Recently, I was invited to speak at Stanford’s MediaX workshop on Metrics. At first, I was curious why I was there, I don’t think of metrics in my day to day life. I think about people and experience and stick figure drawings depicting the negotiation of meaning.

However, if we think about social behaviors and media (and now they relate to uncaptured events in the world): the methodological research becomes an exercise in metrics. What is happening? Is there a singular source event (or a plurality of events)? What do we measure? What does it mean to the source event?…I could go on. But you, gentile readers, can just read the paper or say hi at ACM MM in a few weeks or wait till I post more details about the work.

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