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Contextual semantics for sentiment analysis of Twitter
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Saif, Hassan, He, Yulan, Fernandez, Miriam and Alani, Harith (2016) Contextual semantics for sentiment analysis of Twitter. Information Processing & Management, 52 (1). pp. 5-19. doi:10.1016/j.ipm.2015.01.005 ISSN 0306-4573.
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Official URL: http://dx.doi.org/10.1016/j.ipm.2015.01.005
Abstract
Sentiment analysis on Twitter has attracted much attention recently due to its wide applications in both, commercial and public sectors. In this paper we present SentiCircles, a lexicon-based approach for sentiment analysis on Twitter. Different from typical lexicon-based approaches, which offer a fixed and static prior sentiment polarities of words regardless of their context, SentiCircles takes into account the co-occurrence patterns of words in different contexts in tweets to capture their semantics and update their pre-assigned strength and polarity in sentiment lexicons accordingly. Our approach allows for the detection of sentiment at both entity-level and tweet-level. We evaluate our proposed approach on three Twitter datasets using three different sentiment lexicons to derive word prior sentiments. Results show that our approach significantly outperforms the baselines in accuracy and F-measure for entity-level subjectivity (neutral vs. polar) and polarity (positive vs. negative) detections. For tweet-level sentiment detection, our approach performs better than the state-of-the-art SentiStrength by 4–5% in accuracy in two datasets, but falls marginally behind by 1% in F-measure in the third dataset.
Item Type: | Journal Article | ||||||||||||
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Subjects: | H Social Sciences > HM Sociology P Language and Literature > P Philology. Linguistics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||||||
Library of Congress Subject Headings (LCSH): | Twitter (Firm), Semantics, Internet users -- Attitudes | ||||||||||||
Journal or Publication Title: | Information Processing & Management | ||||||||||||
Publisher: | Elsevier | ||||||||||||
ISSN: | 0306-4573 | ||||||||||||
Official Date: | January 2016 | ||||||||||||
Dates: |
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Volume: | 52 | ||||||||||||
Number: | 1 | ||||||||||||
Page Range: | pp. 5-19 | ||||||||||||
DOI: | 10.1016/j.ipm.2015.01.005 | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
Date of first compliant deposit: | 29 September 2018 | ||||||||||||
Date of first compliant Open Access: | 2 October 2018 | ||||||||||||
RIOXX Funder/Project Grant: |
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