Towards Detecting Rumours in Social Media

TL;DR

This paper presents a methodology and tool for collecting and annotating social media threads to effectively detect rumours during emergencies, addressing limitations of keyword-based methods.

Contribution

It introduces a novel approach for collecting and annotating social media conversations to identify rumours without relying on predefined keywords.

Findings

Effective collection of social media rumours during emergencies

Multiple rumours associated with various stories identified

Method surpasses keyword-based techniques in rumour detection

Abstract

The spread of false rumours during emergencies can jeopardise the well-being of citizens as they are monitoring the stream of news from social media to stay abreast of the latest updates. In this paper, we describe the methodology we have developed within the PHEME project for the collection and sampling of conversational threads, as well as the tool we have developed to facilitate the annotation of these threads so as to identify rumourous ones. We describe the annotation task conducted on threads collected during the 2014 Ferguson unrest and we present and analyse our findings. Our results show that we can collect effectively social media rumours and identify multiple rumours associated with a range of stories that would have been hard to identify by relying on existing techniques that need manual input of rumour-specific keywords.