Analysing how people orient to and spread rumours in social media by looking at conversational threads
- Submitting institution
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Queen Mary University of London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 519
- Type
- D - Journal article
- DOI
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10.1371/journal.pone.0150989
- Title of journal
- PLoS ONE
- Article number
- ARTN e0150989
- First page
- e0150989
- Volume
- 11
- Issue
- 3
- ISSN
- 1932-6203
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 107
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Part of EC FP7-ICT Collaborative Project PHEME (No. 611233), graded excellent, this work performs a thorough analysis of the diffusion of rumours in social media, which subsequently led to developing a novel rumour detection system. Led to co-organising 2 shared tasks in the flagship NLP competition, SemEval (one of these papers, ‘SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours’, cited 107 times), and co-organising 2 workshops (RDSM) co-located with CIKM 2018 (CORE A) and COLING 2020 (CORE A), plus delivering a tutorial on misinformation detection at COLING 2020.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -