A rule dynamics approach to event detection in Twitter with its application to sports and politics
- Submitting institution
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The University of Reading
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 78776
- Type
- D - Journal article
- DOI
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10.1016/j.eswa.2016.02.028
- Title of journal
- Expert Systems with Applications
- Article number
- -
- First page
- 351
- Volume
- 55
- Issue
- -
- ISSN
- 0957-4174
- Open access status
- Out of scope for open access requirements
- Month of publication
- August
- 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)
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9 - DSAI
- Citation count
- 31
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The significance of this paper is that it offers a tool to trace how news events unfold on social media. The novelty about it is that it flags up changes and offers explanations to these changes. Current methods do not flag changes of news events, just detect them. The method was evaluated on real cases and showed an accurate depiction of new events in the real world. It can hence be used to detect significant events in the real-world faster than traditional media.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -