Towards Detecting Rumours in Social Media
April 18, 2015 Β· Declared Dead Β· π AAAI Workshop: AI for Cities
"No code URL or promise found in abstract"
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Authors
Arkaitz Zubiaga, Maria Liakata, Rob Procter, Kalina Bontcheva, Peter Tolmie
arXiv ID
1504.04712
Category
cs.SI: Social & Info Networks
Cross-listed
cs.IR
Citations
96
Venue
AAAI Workshop: AI for Cities
Last Checked
4 months ago
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.
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