A Hybrid Approach to the Sentiment Analysis Problem at the Sentence Level
- Submitting institution
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The University of Huddersfield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 4
- Type
- D - Journal article
- DOI
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10.1016/j.knosys.2016.05.040
- Title of journal
- Knowledge-Based Systems
- Article number
- -
- First page
- 110
- Volume
- 108
- Issue
- -
- ISSN
- 0950-7051
- Open access status
- Technical exception
- Month of publication
- May
- 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
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3
- Research group(s)
-
-
- Citation count
- 78
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Published in the KBS Journal which has an impact factor of 4.396 and a CiteScore of 5.11, the paper is frequently cited as an examplar of sentiment analysis at sentence level and for using a hybrid approach, influencing such works as Nasim et al DOI: 10.1109/ICRIIS.2017.8002475, Singh et al https://link.springer.com/article/10.1007%2Fs12652-018-0862-8 and Nguyen et al https://arxiv.org/abs/1706.08032. For example, the paper's semantic rules based method is used explicitly in Nguyen's deep learning system https://arxiv.org/pdf/1706.08032.pdf
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -