Topic and sentiment aware microblog summarization for twitter

Document Type

Article

Source of Publication

Journal of Intelligent Information Systems

Publication Date

2-1-2020

Abstract

© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Recent advances in microblog content summarization has primarily viewed this task in the context of traditional multi-document summarization techniques where a microblog post or their collection form one document. While these techniques already facilitate information aggregation, categorization and visualization of microblog posts, they fall short in two aspects: i) when summarizing a certain topic from microblog content, not all existing techniques take topic polarity into account. This is an important consideration in that the summarization of a topic should cover all aspects of the topic and hence taking polarity into account (sentiment) can lead to the inclusion of the less popular polarity in the summarization process. ii) Some summarization techniques produce summaries at the topic level. However, it is possible that a given topic can have more than one important aspect that need to have representation in the summarization process. Our work in this paper addresses these two challenges by considering both topic sentiments and topic aspects in tandem. We compare our work with the state of the art Twitter summarization techniques and show that our method is able to outperform existing methods on standard metrics such as ROUGE-1.

ISSN

0925-9902

Publisher

Springer

Volume

54

Issue

1

First Page

129

Last Page

156

Disciplines

Computer Sciences | Social and Behavioral Sciences

Keywords

Microblogging, Summarization, Topic Modeling, Twitter

Scopus ID

85052099240

Indexed in Scopus

yes

Open Access

no

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