Zubiaga, A., Liakata, M., Procter, R. et al. (2 more authors) (2015) Towards Detecting Rumours in Social Media. In: AAAI 2015 Workshop On AI For Cities, 25/01/2015 -26/01/2015, Austin, Texas, USA.
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.
Metadata
Item Type: | Conference or Workshop Item |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 Association for the Advancement of Artificial Intelligence (www.aaai.org). This is an author produced version of a paper subsequently published in Artificial Intelligence for Cities: Papers from the 2015 AAAI Workshop. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | cs.SI; cs.SI; cs.IR |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Feb 2017 16:32 |
Last Modified: | 14 Apr 2017 03:30 |
Published Version: | http://www.aaai.org/ocs/index.php/WS/AAAIW15/paper... |
Status: | Published |
Refereed: | Yes |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:85739 |