Rumour detection model for twitter posts

Abstract

In modern life, social media is playing a vital role; the cutting-edge internet-based life has attracted a huge following. As connectivity and accessibility of networks has amplified it has subsequently increased the use of social media. With the increase in social media accessibility, the speed of spreading rumours i.e. the unverified information has also increased. For detection and interception of rumours over social media a lot of research has been done. Social media has emerged as the most readily accessible and fastest platform for updates related to events happening worldwide. The increase in the use of social media has also increased the misuse of resources for spreading unverified information generally termed as a rumour. The biggest problem in social media is the speed at which the information spreads without verifying its credibility. This research focuses on presenting the present state of the art in automatic rumour detection in social networks. The research highlights the prominent researches done in detecting these rumours in social network over the last many years. The work shows both manual and automatic approaches that can be used. Also, various tools have been identified which were developed for rumour detection in social media platforms. The work also highlights the phase of feature extraction in the rumour detection process i.e. how and why it is significant. The research shows the importance of feature identification by categorizations and finding their impact in the rumour detection process. newline