USING WIKIPEDIA TO PREDICT ELECTION OUTCOMES: ONLINE BEHAVIOR AS A PREDICTOR OF VOTING.

This study seeks to improve election forecasting by supplementing polling data with online information-seeking behavior trends as an indicator of public opinion. Aggregate trends of demonstrations of interest or engagement have been shown to accurately predict behavior trends and reflect public opinion. Further, because traditional poll-based predictions are inherently undermined by self-reporting biases and the intention-behavior disconnect, we can expect that information-seeking trends on widely used social media-as an autonomous and unobtrusive indicator of relative levels of public opinion-can help correct for some of this error and explain unique, additional variance in election results. We advance the literature by using data from Wikipedia pageviews along with polling data in a synthesized model based on the results of the 2008, 2010, and 2012 US Senate general elections. Results show that Wikipedia pageviews data significantly add to the ability of poll-and fundamentals-based projections to predict election results up to 28 weeks prior to Election Day, and benefit predictions most at those early points, when poll-based predictions are weakest. [ABSTRACT FROM AUTHOR]

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