Towards Detecting Rumours in Social Media
This addresses the issue of misinformation spread for citizens and authorities during crises, though it is incremental as it builds on existing rumour detection techniques.
The paper tackled the problem of detecting false rumours in social media during emergencies, such as the 2014 Ferguson unrest, by developing a methodology for collecting conversational threads and a tool for annotation, resulting in effective identification of multiple rumours without manual keyword input.
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.