Topic-Specific Stylistic Variations for Opinion Retrieval on Twitter

Anastasia Giachanou, Morgan Harvey, Fabio Crestani

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

8 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationAdvances in Information Retrieval, 38th European Conference on IR Research, ECIR 2016
EditorsN. Ferro, F. Crestani, M.-F. Meons, J. Mothe, F. Silvestri, G. M. Di Nunzio, C. Hauff, G. Silvello
Place of PublicationLondon
PublisherSpringer
Pages466-478
ISBN (Print)978-3-319-30670-4
DOIs
Publication statusPublished - Apr 2016

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