Rumor Detection System for Twitter (A Micro-Blogging Site)

Abstract

Micro-blog provides a platform for the users to transfer their thoughts and information in limited words more expressively. Its concise and easy to access nature makes it popular among every age group. Inspite, of all its pros and popularity, some people use it to achieve their bad motives i.e. to misguide people and create violence. To overcome this problem a system is required that will help to detect fake tweets in a limited amount of time. In this paper, a feature based approach for rumor detection has been proposed. The proposed approach utilizes 9 features which shows author as well as readers reaction to identify rumor tweets which may differ for different users in different situations. For experimentation synthetic data and from Pheme has been utilize. A comparative study of the approach for the datasets has been done on the basis of evaluation parameters Recall, Precision and f-measure. Satisfactory results have been obtained for Pheme data with less number of features as compare to synthetic dataset.