This document summarizes research on using Twitter for live event annotation and discussion. Key findings include: - Tweets during live events allow for implicit annotation through hashtags, mentions and retweets. Volume of tweets peaks during events and discussion surges after. - Automatic analysis of tweet volumes can detect segment boundaries in events with 92% accuracy compared to editorialized summaries. - Mentions create directed networks showing influence, while hashtags group tweets by topic. Central figures and communities form around events. - Future work includes sentiment analysis, topic trends over time, and using tweets to understand events without source material. Tweets provide indirect annotation of and reaction to events through social discussion.

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