Moral panics and fear of crime around terrorism in the online world of Twitter

Abstract

In the past decade social media platforms have risen to exceptional levels of prominence in societies across the globe. Platforms such as Twitter allow millions of users from across the globe to contribute to various discussions, from menial everyday occurrences to events of extreme violence that appear in the media. Twitter has also allowed for public figures (politicians, celebrities, academics, and so forth) to converse more directly with the general public. A non-directional hypothesis was used to guide the question of determining how moral panics impact discussion around terrorism on Twitter. This study analyzed discourse from Twitter which took place in the two weeks following the terror attack which occurred in Nice France in July of 2016. Two data-sets were collecting using a new platform called Active Tweet Retrieval-Visualization (ATR-Vis) which relies on data-mining and machine learning algorithm to collect and sort relevant data from Twitter. By looking at data from Twitter and performing a frequency based content analysis of five categories words and phrases relevant to moral panics and terrorism it was found that fear of crime and moral panic pervades into social media discussions. The study concludes that more work is needed in determining how online discourse can impact anti-terror legislative decisions.