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2015 | OriginalPaper | Buchkapitel

The Pareto Principle Is Everywhere: Finding Informative Sentences for Opinion Summarization Through Leader Detection

verfasst von : Linhong Zhu, Sheng Gao, Sinno Jialin Pan, Haizhou Li, Dingxiong Deng, Cyrus Shahabi

Erschienen in: Recommendation and Search in Social Networks

Verlag: Springer International Publishing

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Abstract

Most previous works on opinion summarization focus on summarizing sentiment polarity distribution toward different aspects of an entity (e.g., battery life and screen of a mobile phone). However, users’ demand may be more beyond this kind of opinion summarization. Besides such coarse-grained summarization on aspects, one may prefer to read detailed but concise text of the opinion data for more information. In this paper, we propose a new framework for opinion summarization. Our goal is to assist users to get helpful opinion suggestions from reviews by only reading a short summary with a few informative sentences, where the quality of summary is evaluated in terms of both aspect coverage and viewpoints preservation. More specifically, we formulate the informative sentence selection problem in opinion summarization as a community leader detection problem, where a community consists of a cluster of sentences toward the same aspect of an entity and leaders can be considered as the most informative sentences of the corresponding aspect. We develop two effective algorithms to identify communities and leaders. Reviews of six products from Amazon.com are used to verify the effectiveness of our method for opinion summarization.

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Vorheriges Kapitel Personalization of Web Search Using Social Signals

Nächstes Kapitel Social Media Question Asking: A Developing Country Perspective

http://www.tripadvisor.com/.

Note that \(|\mathcal {N}_{k}(s)|\) can be larger than \(k\) since there could be the event of ties (i.e., a set of neighbors have the same similarity to \(s\)).

Available at http://sites.google.com/site/linhongi2r/data-and-code.

A longer summary is more likely to provide better information but is less concise.

ROUGE-N is a popular toolkit which measures the quality of a summary by comparing it to other reference summaries using \(n\)-gram co-occurrence.

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Titel: The Pareto Principle Is Everywhere: Finding Informative Sentences for Opinion Summarization Through Leader Detection
verfasst von: Linhong Zhu
Sheng Gao
Sinno Jialin Pan
Haizhou Li
Dingxiong Deng
Cyrus Shahabi
Verlag: Springer International Publishing
Buch: Recommendation and Search in Social Networks
Print ISBN: 978-3-319-14378-1

Electronic ISBN: 978-3-319-14379-8

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-14379-8_9

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