Topic-Specific Stylistic Variations for Opinion Retrieval on Twitter

Giachanou, Anastasia, Harvey, Morgan and Crestani, Fabio (2016) Topic-Specific Stylistic Variations for Opinion Retrieval on Twitter. In: Advances in Information Retrieval, 38th European Conference on IR Research, ECIR 2016. Springer, London, pp. 466-478. ISBN 978-3-319-30670-4

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Official URL: http://dx.doi.org/10.1007/978-3-319-30671-1_34

Abstract

Twitter has emerged as a popular platform for sharing information and expressing opinions. Twitter opinion retrieval is recognized as a powerful tool for finding people's attitudes on different topics. However, the vast amount of data and the informal language of tweets make opinion retrieval on Twitter very challenging. In this paper, we propose to leverage topic-specific stylistic variations to retrieve tweets that are both relevant and opinionated about a particular topic. Experimental results show that integrating topic specific textual meta-communications, such as emoticons and emphatic lengthening in a ranking function can significantly improve opinion retrieval performance on Twitter.

Item Type: Book Section
Subjects: G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
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Depositing User: Morgan Harvey
Date Deposited: 04 Feb 2016 14:11
Last Modified: 11 May 2017 19:07
URI: http://nrl.northumbria.ac.uk/id/eprint/25863

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