Opinion mining and sentiment analysis Export

@article{pang2008omsa, 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.}, author = {Pang, Bo and Lee, Lillian}, citeulike-article-id = {3135824}, citeulike-linkout-0 = {http://www.cs.cornell.edu/home/llee/opinion-mining-sentiment-analysis-survey.html}, citeulike-linkout-1 = {http://dx.doi.org/http:/dx.doi.org/10.1561/1500000001}, doi = {http:/dx.doi.org/10.1561/1500000001}, journal = {Foundation and Trends in Information Retrieval}, keywords = {opinion, opinion-mining, sentiment, sentiment-extraction, subjectivity, summarisation, summarization, survey, text, text-analytics, text-mining}, number = {1-2}, pages = {1--135}, posted-at = {2008-08-19 16:29:08}, priority = {4}, title = {Opinion mining and sentiment analysis}, url = {http://dx.doi.org/http:/dx.doi.org/10.1561/1500000001}, volume = {2}, year = {2008} }

TY - JOUR ID - pang2008omsa L3 - citeulike-article-id:3135824 N2 - 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. IS - 1-2 JF - Foundation and Trends in Information Retrieval EP - 135 TI - Opinion mining and sentiment analysis VL - 2 SP - 1 KW - opinion KW - opinion-mining KW - sentiment KW - sentiment-extraction KW - subjectivity KW - summarisation KW - summarization KW - survey KW - text KW - text-analytics KW - text-mining AU - Pang, Bo AU - Lee, Lillian PY - 2008/// UR - http://dx.doi.org/http:/dx.doi.org/10.1561/1500000001 ER -