THANOS: A Predictive Model of Electoral Campaigns using Twitter Data and Opinion Polls

Music City Center 

The influence and impact of social media campaigns on democratic elections is a critical area of research in modern big-data analytics. While the efficacy of using social media data for forecasting election results has been debated in political and social science literature, this paper introduces a novel modeling approach that combines public opinion polls with Twitter data, incorporating key network structure features of Twitter to enhance prediction accuracy. We developed two models: the Twitter Hashtag based Opinion Survey (THOS) model, which uses hashtag frequency, and the Twitter Hashtag and Network-based Opinion Survey (THANOS) model, which includes network centrality measures. Applying these models to Ireland's 36th amendment referendum and the 2018 US Senate elections yielded promising results. The THOS model effectively predicted outcomes in races with clear frontrunners, while the THANOS model excelled in closely contested races by leveraging network dynamics. These findings underscore the potential of integrating social media data with traditional polls to improve electoral forecasts, demonstrating the robust capabilities of the THOS and THANOS models in providing accurate predictions based on the interplay of public opinion and social media activity.