An Approach to Extract New Keywords From Radical Groups in Social Networks

Abstract

In recent times, numerous users as well as communities on social networks post messages in multimedia formats. The significant part of the message is the keyword that would help in recognizing the theme of information. Hence, this research aims to determine the new keywords occur in the messages posted on social network which would also be beneficial in identifying the category of user, various communities, and hidden patterns exist in the social network. In this paper, probabilistic approach is applied to identify the new keywords from the radical groups. Radical groups are those whose demeanor is totally opposite to the acceptance of community, for instance, terrorist groups. Hence, the dataset of terrorist community extracted from Twitter is used to find the new keywords that occur for a short span of time. State-of-the-art studies carried out the identification of terrorist communities based on keywords already present in lexicon, but the proposed approach makes the decision on the basis of both old as well as new keywords.