Towards Detecting Rumours in Social Media

This paper describes the methodology that the authors have developed for the collection and sampling of conversational threads, as well as the tools they have developed to identify rumour-based threads. They describe the annotation task conducted on threads collected during the 2014 Ferguson unrest and present and analyse their findings throughout the section. 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, and the authors’ results show that it is possible to effectively collect 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.

Practitioners will find this research useful for streamlining their own systems of vetting social media information during emergencies. Scholars exploring new developments in the topic, and especially those interested in the Ferguson case study, will also find it useful.