Towards Opinion Summarization from Online Forums

Summarizing opinions expressed in online forums can potentially benefit many people. However, special characteristics of this problem may require changes to standard text summarization techniques. In this work, we present our initial attempt at extractive summarization of opinionated online forum th...

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Main Authors: DING YING, Jing JIANG
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2015
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Online Access:https://ink.library.smu.edu.sg/sis_research/3072
https://ink.library.smu.edu.sg/context/sis_research/article/4072/viewcontent/P_ID_52347_R15_TowardsOpinionSummOnlineForums.pdf
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spelling sg-smu-ink.sis_research-40722016-02-18T01:39:46Z Towards Opinion Summarization from Online Forums DING YING, Jing JIANG, Summarizing opinions expressed in online forums can potentially benefit many people. However, special characteristics of this problem may require changes to standard text summarization techniques. In this work, we present our initial attempt at extractive summarization of opinionated online forum threads. Given the nature of user generated content in online discussion forums, we hypothesize that besides relevance, text quality and subjectivity also play important roles in deciding which sentences are good summary sentences. We therefore construct an annotated corpus to facilitate our study of extractive summarization of online discussion forums. We define a set of features to capture relevance, text quality and subjectivity, and empirically test their usefulness in choosing summary sentences. Using unpaired Student's t-test, we find that sentence length and number of sentiment words have high correlations with good summary sentences. Finally we propose some simple modifications to a standard Integer Linear Programming based summarization framework to incorporate these features. 2015-09-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3072 https://ink.library.smu.edu.sg/context/sis_research/article/4072/viewcontent/P_ID_52347_R15_TowardsOpinionSummOnlineForums.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computational linguistics Integer programming Online systems Social networking (online) Text processing Extractive summarizations Integer Linear Programming Online discussion forums Sentence length Simple modifications Student's t tests Text summarization User-generated content Databases and Information Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Computational linguistics
Integer programming
Online systems
Social networking (online)
Text processing
Extractive summarizations
Integer Linear Programming
Online discussion forums
Sentence length
Simple modifications
Student's t tests
Text summarization
User-generated content
Databases and Information Systems
spellingShingle Computational linguistics
Integer programming
Online systems
Social networking (online)
Text processing
Extractive summarizations
Integer Linear Programming
Online discussion forums
Sentence length
Simple modifications
Student's t tests
Text summarization
User-generated content
Databases and Information Systems
DING YING,
Jing JIANG,
Towards Opinion Summarization from Online Forums
description Summarizing opinions expressed in online forums can potentially benefit many people. However, special characteristics of this problem may require changes to standard text summarization techniques. In this work, we present our initial attempt at extractive summarization of opinionated online forum threads. Given the nature of user generated content in online discussion forums, we hypothesize that besides relevance, text quality and subjectivity also play important roles in deciding which sentences are good summary sentences. We therefore construct an annotated corpus to facilitate our study of extractive summarization of online discussion forums. We define a set of features to capture relevance, text quality and subjectivity, and empirically test their usefulness in choosing summary sentences. Using unpaired Student's t-test, we find that sentence length and number of sentiment words have high correlations with good summary sentences. Finally we propose some simple modifications to a standard Integer Linear Programming based summarization framework to incorporate these features.
format text
author DING YING,
Jing JIANG,
author_facet DING YING,
Jing JIANG,
author_sort DING YING,
title Towards Opinion Summarization from Online Forums
title_short Towards Opinion Summarization from Online Forums
title_full Towards Opinion Summarization from Online Forums
title_fullStr Towards Opinion Summarization from Online Forums
title_full_unstemmed Towards Opinion Summarization from Online Forums
title_sort towards opinion summarization from online forums
publisher Institutional Knowledge at Singapore Management University
publishDate 2015
url https://ink.library.smu.edu.sg/sis_research/3072
https://ink.library.smu.edu.sg/context/sis_research/article/4072/viewcontent/P_ID_52347_R15_TowardsOpinionSummOnlineForums.pdf
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