more tweets, more votes: social media as a quantitative indicator of political behavior
Unit of analysis: US House elections in 2010 and 2012. X-Axis: (# of tweets mentioning the GOP candidate)/(# of tweets mentioning either major party candidate). Y-axis: GOP margin of victory.
I have a new working paper with Joe DiGrazia*, Karissa McKelvey and Johan Bollen asking if social media data actually forecasts offline behavior. The abstract:
Is social media a valid indicator of political behavior? We answer this question using a random sample of 537,231,508 tweets from August 1 to November 1, 2010 and data from 406 competitive U.S. congressional elections provided by the Federal Election Commission. Our results show that the percentage of Republican-candidate name mentions correlates with the Republican vote margin in the subsequent election. This finding persists even when controlling for incumbency, district partisanship, media coverage of the race, time, and demographic variables such as the district’s racial and gender composition. With over 500 million active users in 2012, Twitter now represents a new frontier for the study of human behavior. This research provides a framework for incorporating this emerging medium into the computational social science toolkit.
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Unit of analysis: US House elections in 2010 and 2012. X-Axis: (# of tweets mentioning the GOP candidate)/(# of tweets mentioning either major party candidate). Y-axis: GOP margin of victory.
I have a new working paper with Joe DiGrazia*, Karissa McKelvey and Johan Bollen asking if social media data actually forecasts offline behavior. The abstract:
Is social media a valid indicator of political behavior? We answer this question using a random sample of 537,231,508 tweets from August 1 to November 1, 2010 and data from 406 competitive U.S. congressional elections provided by the Federal Election Commission. Our results show that the percentage of Republican-candidate name mentions correlates with the Republican vote margin in the subsequent election. This finding persists even when controlling for incumbency, district partisanship, media coverage of the race, time, and demographic variables such as the district’s racial and gender composition. With over 500 million active users in 2012, Twitter now represents a new frontier for the study of human behavior. This research provides a framework for incorporating this emerging medium into the computational social science toolkit.