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SentiCircles for contextual and conceptual semantic sentiment analysis of Twitter

Saif, Hassan; Fernández, Miriam; He, Yulan and Alani, Harith (2014). SentiCircles for contextual and conceptual semantic sentiment analysis of Twitter. In: The Semantic Web: Trends and Challenges: 11th International Conference, ESWC 2014, Anissaras, Crete, Greece, May 25-29, 2014. Proceedings, Lecture Notes in Computer Science, Springer Internatioal Publishing, pp. 83–98.

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URL: http://2014.eswc-conferences.org/
DOI (Digital Object Identifier) Link: https://doi.org/10.1007/978-3-319-07443-6_7
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Abstract

Lexicon-based approaches to Twitter sentiment analysis are gaining much popularity due to their simplicity, domain independence, and relatively good performance. These approaches rely on sentiment lexicons, where a collection of words are marked with fixed sentiment polarities. However, words’ sentiment orientation (positive, neural, negative) and/or sentiment strengths could change depending on context and targeted entities. In this paper we present SentiCircle; a novel lexicon-based approach that takes into account the contextual and conceptual semantics of words when calculating their sentiment orientation and strength in Twitter. We evaluate our approach on three Twitter datasets using three different sentiment lexicons. Results show that our approach significantly outperforms two lexicon baselines. Results are competitive but inconclusive when comparing to state-of-art SentiStrength, and vary from one dataset to another. SentiCircle outperforms SentiStrength in accuracy on average, but falls marginally behind in F-measure.

Item Type: Conference or Workshop Item
Copyright Holders: 2014 Springer International Publishing Switzerland
ISBN: 3-319-07442-3, 978-3-319-07442-9
Project Funding Details:
Funded Project NameProject IDFunding Body
EU-FP7 project SENSE4USGrant no. 611242EU
Keywords: #eswc2014Saif; sentiment analysis; semantics; Twitter
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 40661
Depositing User: Kay Dave
Date Deposited: 06 Aug 2014 08:10
Last Modified: 12 Sep 2018 07:19
URI: http://oro.open.ac.uk/id/eprint/40661
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