Social Network Structure as a Predictor of Social Behavior: The Case of Protest in the 2016 US Presidential Election

摘要

This research explores relationships between social network structure (as inferred from Twitter posts) and the occurrence of domestic protests following the 2016 US Presidential Election. A hindcasting method is presented which exploits Random Forest classification models to generate predictions about protest occurrence that are then compared to ground truth data. Results show a relationship between social network structure and the occurrence of protests that is stronger or weaker depending on the time frame of prediction.