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Vocal Minority vs. Silent Majority Eni Mustafaraj Samantha Finn Carolyn Whitlock Panagiotis Metaxas IEEE SocialCom 2011 @ MIT Media Lab October 10, 2011
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Gaming How humans can use technology to “influence” the political process.
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Examples of gaming Vocal Minority can: 1.Frame the conversation 2.Put pressure on the media
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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.
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2008: Election of President Obama
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2009: The Healthcare Reform
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2009: The rise of Tea Party
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Aug 2009: Senator Kennedy Dies
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Special Election in MA Martha Coakley Democrat Attorney General Scott Brown Republican State Senator
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Pre-electoral Polls Boston Globe01-04-201050%35% Rasmussen Reports01-04-201050%41% Rasmussen Reports01-11-201049%47%
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Twitter Data Collection January 13 – 20, 2010 234,697 tweets 56,165 unique Twitter users
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Vocal vs. Silent Silent users (1 tweet) Vocal users (50+ tweets) Silent users Vocal users User Volume Tweets Volume
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Political Activism Friendship graph for 574 users with more than 50 tweets
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Tweets are not made equal
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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%
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Framing the Conversation
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Social Media Campaigns
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115 tweets to report progress on Facebook fans 54 tweets to report progress on Twitter followers
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Campaign Amplification
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Targeting the Media
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Political Tweetbots
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Human Bots?
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30 lists with tweets 2758 tweets 180 media accounts targeted.
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Pre-Fabricated Tweets
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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
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Conclusions Tweets are not equal. Opinion mining and predictions based on aggregated data cannot be trusted.
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Tweets Factory 2.0
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Thank you #questions
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