Predicting Political Polarization from Cyberbalkanization: Time series analysis of Facebook pages and Opinion Poll during the Hong Kong Occupy Movement

Abstract

The purpose of this study is to investigate the temporal association between cyberbalkanization and real life polarization of public opinion during the Hong Kong Occupy Movement in 2014. 1,387 Facebook Pages about Hong Kong during July 1 to December 15, 2014 were collected, their publicly accessible posts were retrieved, and a post sharing network (1,397 nodes and 41,404 edges) was constructed. Network communities were computationally extracted to determine the community membership for each Facebook page. Daily degree of cyberbalkanization was quantified with the number of sharings through strong ties (intra-community sharing) connections. The level of political polarization was derived from the opinion polls data with the proportion of respondents who gave extreme ratings to the government leader in Hong Kong. In a time series analysis, the daily degree of cyberbalkanization, as measured by the number of sharing through the strong ties, was significantly associated with the level of political polarization, particularly with the younger age group's opinion poll result. This is the first study that provides empirical evidence for supporting cyberbalkanization to serve as a leading predictive indicator of the polarization of public opinion for at least 10 days ahead, suggesting that social media data analysis can supplement traditional public opinion research methods, such as phone survey, during social controversy.