Detection of Social Bots: Quantification of Language Independent Features and Bot Clusters

Abstract

With the advent of social media, social bots—computer programs that automatically post news—have become popular, and some of these have been purposefully used to disseminate fake news. This is an increasingly serious problem in the digital era. Although a lot of bot detection methods have been proposed, such methods often cannot overcome their language dependencies and fail to find bot clusters. This research aims at constructing a language-independent method for detecting social bots and their clusters on Twitter using machine learning. The results provide new information available for the development of such methods.