Publication | Closed Access
Forecasting Congressional Elections Using Facebook Data
33
Citations
19
References
2015
Year
Facebook DataFacebook StatisticsPublic OpinionPolitical PolarizationPolitical BehaviorFacebook MetricsSmart VotingSocial SciencesSocial MediaSocial Medium NewsPolitical CommunicationStatisticsElection ForecastingPolitical PartiesPredictive AnalyticsForecastingPolitical AttitudesPolitical CampaignsMobilization MetricsSocial Medium DataArtsPolitical Science
ABSTRACT Facebook constantly tracks the growth of each congressional candidate’s fan base and the number of people engaging with candidates online. These Facebook metrics comprise a rich dataset that theoretically may capture the effectiveness of campaigns in building participatory support as well as their potential to mobilize support. When added to electoral fundamentals similar to those used in national-election forecasting, can Facebook data be used to develop a reliable model for predicting vote-percentage outcomes of individual congressional contests? The results of an exploratory investigation reveal that fan participation and mobilization metrics tracked by Facebook produced surprisingly accurate election predictions in the 2012 US Senate races studied. The question remains, however, whether these results are a “flash in the 2012 pan” or an indication that using Facebook statistics to measure campaign effectiveness is a new tool that scholars can use to forecast the outcome of congressional campaigns.
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