Contextual sentiment analysis for social media genres.
- Submitting institution
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Robert Gordon University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- Wiratunga_2
- Type
- D - Journal article
- DOI
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10.1016/j.knosys.2016.05.032
- Title of journal
- Knowledge-Based Systems
- Article number
- -
- First page
- 92
- Volume
- 108
- Issue
- -
- ISSN
- 1872-7409
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2016
- URL
-
-
- 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
-
-
- Research group(s)
-
-
- Citation count
- 51
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is cited by editors as a key approach to contextual sentiment analysis for social media genres. The novel use of sentiment in reviews for product recommendation presented here led to the collaboration with Professor Enric Plaza ( https://www.iiia.csic.es/~enric/Enric-IIIA/Enric_%40_IIIA.html) and a joint publication (DOI 10.1007/978-3-319-24586-7_5). The work also led to further collaborative projects with city councils, first in Aberdeen analysing Twitter feeds, then in Dundee with the Dundee Tourism Partnership (https://www.d-tag.co.uk/) on social media sentiment across Dundee and Angus. The group (tourism@dundee.com), led by gaynor.sullivan@dundeecity.gov.uk was able to successfully secure £20K to take this work forward.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -