AUGUR: Forecasting the Emergence of New Research Topics
- Submitting institution
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The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1587485
- Type
- E - Conference contribution
- DOI
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10.1145/3197026.3197052
- Title of conference / published proceedings
- JCDL ’18: The 18th ACM/IEEE Joint Conference on Digital Libraries
- First page
- 303
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- May
- Year of publication
- 2018
- URL
-
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- Supplementary information
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-
- 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
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2
- Research group(s)
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-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper, accepted at a premiere venue for Digital Library research, presents the first approach able to predict the emergence of a new research area, before its explicit recognition by a research community. Technically, the approach improves over the Clique Percolation Method by returning fine-grained clusters in dense networks. Significance extends beyond Computer Science, as this work provides new evidence of a link between topological changes in scientific collaboration networks and the emergence of new areas. Led to a grant from Springer (Editorial Director, details on request, contract signed in 2021) aiming to equip editors with a horizon scanning solution.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -