Foundations and Trends® in Information Retrieval > Vol 2 > Issue 1–2

Opinion Mining and Sentiment Analysis

Bo Pang, Yahoo! Research, USA, bopang@yahoo-inc.com Lillian Lee, Computer Science Department, Cornell University, USA, llee@cs.cornell.edu
 
Suggested Citation
Bo Pang and Lillian Lee (2008), "Opinion Mining and Sentiment Analysis", Foundations and Trends® in Information Retrieval: Vol. 2: No. 1–2, pp 1-135. http://dx.doi.org/10.1561/1500000011

Published: 07 Jul 2008
© 2008 B. Pang and L. Lee
 
Subjects
Data mining,  Information extraction
 
Download article
In this article:
1 Introduction
2 Applications
3 General Challenges
4 Classification and Extraction
5 Summarization
6 Broader Implications
7 Publicly Available Resources
8 Concluding Remarks
References

Abstract

An important part of our information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges arise as people now can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden eruption of activity in the area of opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object.

This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. Our focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. We include material on summarization of evaluative text and on broader issues regarding privacy, manipulation, and economic impact that the development of opinion-oriented information-access services gives rise to. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided.

DOI:10.1561/1500000011
ISBN: 978-1-60198-150-9
148 pp. $99.00
Buy book
 
ISBN: 978-1-60198-151-6
148 pp. $125.00
Buy E-book
Table of contents:
1: Introduction
2: Applications
3: General Challenges
4: Classification and Extraction
5: Summarization
6: Broader Implications
7: Publicly Available Resources
8: Concluding Remarks
References

Opinion Mining and Sentiment Analysis

An important part of our information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges arise as people can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden eruption of activity in the area of opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object. Opinion Mining and Sentiment Analysis covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. The focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. The survey includes an enumeration of the various applications, a look at general challenges and discusses categorization, extraction and summarization. Finally, it moves beyond just the technical issues, devoting significant attention to the broader implications that the development of opinion-oriented information-access services have: questions of privacy, vulnerability to manipulation, and whether or not reviews can have measurable economic impact. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided. Opinion Mining and Sentiment Analysis is the first such comprehensive survey of this vibrant and important research area and will be of interest to anyone with an interest in opinion-oriented information-seeking systems.

 
INR-011