Analysis of Techniques for Rumor Detection in Social Media

Abstract

The ubiquitous nature of social media platforms resulted into generation of large amount of multimedia data in social networks. The openness and unrestricted way to share the information on social media platforms fosters information spread across the network regardless of its credibility. Such kind of spreading the misinformation happens usually in the context of breaking news. Due to unverified information, such misinformation, also known as rumors may cause severe damages. Despite overwhelming use, uncontrolled nature of social media platforms usually results in generation and unfold of rumors. Therefore, automatically detecting the rumors from social media platforms is one of the highly sought-after research area in the domain of social media analytics. Motivated by the same, this paper focuses on detailed discussion of datasets and state-of-the-art approaches of rumor detection. Moreover, this paper sheds light upon supervised and unsupervised methods and deep learning approaches for rumor detection.