Tweet the Debates

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    Notes on slide 1

    There is MORE to tagging and comments in social media than how we think of it currently as the single browser/site/startup.

    These tags and comments are regulated to anchored explicit annotation. This is the problem. Temporally, there is a gap – we cannot leverage these components like we have with photos.

    Several sites (including YouTube and my own past research) tried to make deep comments prevalent.

    Enter Twitter. (explain it quickly) With twitter, when something happens and you wanna shout, you tweet.

    Many People Tweet while they watch tv, many TV shows call for people to follow the twitter stream.

    (this is a fake tweet)

    Not only of the tweet to the video but the rich data within the tweet.

    Some techniques from may be applicable: Wei Hao Lin, Alexander Haputmann: Identifying News Videos ideological viewpoint or bias

    Favorites, Groups & Events

    Tweet the Debates - Presentation Transcript

    1. Tweet the Debates
      David A. Shamma,
      Lyndon Kennedy,
      Elizabeth F. Churchill
      Internet Experiences
      Yahoo! Research
    2. Internet Experiences GroupYahoo! Research
      (David) AymanShamma
      Lyndon Kennedy
      Elizabeth Churchill
    3. Traditional Video
    4. Traditional Comments and Tags
      Left in Whole, Unattached.
    5. Some tags can be added as annotations
      Post annotations don’t allow for real time commentary.
      This part is interesting.
    6. Social Conversations happen around videos
      Well – actually people join in a session and converse afterwards.
    7. Social and Live Performance
      DJs manage three social networks through group of mediums like: MySpace, Webcasts, Twitter, Facebook, and IM.
    8. Much of Social Media is about Congregation
      Something we think about at CHI and CSCW.
      (if you are so definition inclined you can enjoy the above paste)
    9. A new form of indirect media-object annotation.
      中国没有Twitter
    10. People Tweet While They Watch
    11. @kanye dude, not cool #vma
      Tweeting while watching offers implicit event annotation…one in need of media reification.
    12. CurrentTV: Hack the Debate
    13. a Tweet
      RT: @jowyang If you are watching the debate you’re
      invited to participate in #tweetdebate Here is the 411
      http://tinyurl.com/3jdy67
    14. Anatomy of a Tweet
      Repeated (retweet) content starts with RT
      Address other users with an @
      RT: @jowyang If you are watching the debate you’re
      invited to participate in #tweetdebate Here is the 411
      http://tinyurl.com/3jdy67
      Rich Media embeds via links
      Tags start with #
    15. Indirect Annotation
      Sept 26, 2009 18:23 EST
      RT: @jowyang If you are watching the debate you’re
      invited to participate in #tweetdebate Here is the 411
      http://tinyurl.com/3jdy67
    16. Tweet Crawl
      Three hashtags: #current #debate08 #tweetdebate
      97 mins debate + 53 mins following = 2.5 hours total.
      3,238 tweets from 1,160 people.
      1,824 tweets from 647 people during the debate.
      1,414 tweets from 738 people post debate.
      577 @ mentions (reciprocity!)
      266 mentions during the debate
      311 afterwards.
      Low RT: 24 retweetsin total
      6 during
      18 afterwards.
    17. Volume of Tweets by Minute
      Crawled from the Twitter RESTful search API.
    18. Tweets During and After the Debates
      Conversation swells after the debate.
    19. Volume of Conversation Follows the Debate
      Post debate
    20. Does Conversation follow After a Segment
      Think of Isaac Newton
      Post Segment?
    21. Will the roots of f’(x) find segmentation markers?
    22. Automatic Segment Detection
      We use Newton’s Method to find extrema outside μ±σ to find candidate markers. Any marker that follows from the a marker on the previous minute is ignored.
    23. Automatic Segment Detection with 92% Accuracy
      When compared to CSPAN’s editorialized Debate Summary ± 1 minute.
    24. Tags As Boundary Objects
    25. Directed Communication via @mentions
      John Tweets: “Hey @mary, my person is winning!” Makes a directed graph from John to Mary.
    26. Barack, NewsHour, & McCain automatically discovered.
      High Eigenvector Centrality Figures on Twitter from the First US Presidential Debate of 2008.
    27. Sinks in the network
      High in degree but poor centrality.
    28. Tweets to Terms
      Common stems in bold-italic.
    29. Tweets are Reaction not Content
    30. HCC and MM Findings & Future Work
      Indirect annotation through community action
      Uncollected Sources (read: events) are highly valuable
      Segmentation
      Figure Identification
      Term Distance
      What about Sentiment? Onset? Trends? Sustained Topics?
    31. Argentina v England (1986 FIFA World Cup quarter-final)
    32. Nooo! #worldcup #hand
      Event Onset!
    33. July 20, 1969 Apollo 11 Moon Landing
    34. omg! @nasarukddng? #landing #fake #moon
      Tags as boundary objects can find communities & sets.
    35. Godzilla attacking the Tokyo
    36. やばい!国会議事堂をつぶしている!@radonがんばって!#gojira
      Tweet Content Comprehension Need Not Be Needed.
    37. Statler
      http://bit.ly/statler
    38. Thanks Chloe S., Ben C., Marc S., M. Cameron J., Ryan S.!
      @paulr they are coming #2
      The midnight ride of Paul Revere
    SlideShare Zeitgeist 2009

    + David ShammaDavid Shamma Nominate

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    From my talk at the Social Media Workshop at ACM MM more

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