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Vocal Minority vs. Silent Majority Eni Mustafaraj Samantha Finn Carolyn Whitlock Panagiotis Metaxas IEEE SocialCom MIT Media Lab October 10, 2011.

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Presentation on theme: "Vocal Minority vs. Silent Majority Eni Mustafaraj Samantha Finn Carolyn Whitlock Panagiotis Metaxas IEEE SocialCom MIT Media Lab October 10, 2011."— Presentation transcript:

1 Vocal Minority vs. Silent Majority Eni Mustafaraj Samantha Finn Carolyn Whitlock Panagiotis Metaxas IEEE SocialCom 2011 @ MIT Media Lab October 10, 2011

2 Gaming How humans can use technology to “influence” the political process.

3 Examples of gaming Vocal Minority can: 1.Frame the conversation 2.Put pressure on the media

4 Implications Not all user-generated content is equal. The fact that we have lots of it, doesn’t mean we should use it as it is.

5 2008: Election of President Obama

6 2009: The Healthcare Reform

7 2009: The rise of Tea Party

8 Aug 2009: Senator Kennedy Dies

9 Special Election in MA Martha Coakley Democrat Attorney General Scott Brown Republican State Senator

10 Pre-electoral Polls Boston Globe01-04-201050%35% Rasmussen Reports01-04-201050%41% Rasmussen Reports01-11-201049%47%

11 Twitter Data Collection  January 13 – 20, 2010  234,697 tweets  56,165 unique Twitter users

12 Vocal vs. Silent Silent users (1 tweet) Vocal users (50+ tweets) Silent users Vocal users User Volume Tweets Volume

13 Political Activism Friendship graph for 574 users with more than 50 tweets

14 Tweets are not made equal

15

16 What’s in a Tweet? Silent UsersVocal Users Only Text42.0% 8.0% Hashtags14.1%53.0% Links29.7%49.4% Retweets29.6%60.3%

17 Framing the Conversation

18 Social Media Campaigns

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20 115 tweets to report progress on Facebook fans 54 tweets to report progress on Twitter followers

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22 Campaign Amplification

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25 Targeting the Media

26 Political Tweetbots

27 Human Bots?

28 30 lists with tweets 2758 tweets 180 media accounts targeted.

29 Pre-Fabricated Tweets

30 The Tweets-Factory against Media DO YOUR JOB SHINE THE LIGHT ON ACORN http://bit.ly/DoYourJob @ACORN Nat @SEIU @GlobeSenateRace @wwlp #masen WE THE PEOPLE WANT A FAIR ELECTION http://bit.ly/acRNFraud @ACORN Nat @SEIU @GlobeSenateRace @wwlp #masen

31

32 Conclusions  Tweets are not equal.  Opinion mining and predictions based on aggregated data cannot be trusted.

33 Tweets Factory 2.0

34 Thank you #questions


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