Keyword-Based Approach for Detecting Civil Unrest Events from Social Media

Abstract

In recent years the various online social media platforms like Twitter, Facebook, and Google+ are much popular and this popularity makes the protesters to actively use social media during civil unrest to express their opinions of the remonstrance, communicate their plans, and organize future events, which yield an impressive amount of data that has been used by the researchers to predict the protest activity in near future. Effective detection of such potentially dangerous misinformation can help to ensure the safety of the public with minimum disruption. We identified the correlation between the tweets promoting protest and the imminent protest activity. Thus we proposed a keyword-based approach for analyzing the behavior of a civil unrest event and also build a probabilistic model for classifying civil unrest events. Extensive experimental evaluations were done on the Twitter dataset from #Jallikattu, #BusFareHike and #SaveFisherMen civil unrest to demonstrate the effectiveness and efficiency of our proposed approach.