A Survey of Opinion Mining and Sentiment Analysis
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TLDR
A survey is presented which covers the problem of sentiment analysis, techniques and methods used for the same and the major challenge lies in analyzing the sentiments and identifying emotions expressed in texts.Abstract:
A huge amount of online information, rich web resources are highly unstructured and such natural language are not solvable by machine directly. The increased demand to capture opinions of general public about social events, campaigns and sales of the product has led to study of the field opinion mining and sentiment analysis. Opinion refers to extraction of lines in raw data which expresses an opinion. Sentiment analysis identifies polarity of extracted opinions. The major challenge lies in analyzing the sentiments and identifying emotions expressed in texts. This paper presents a survey which covers a problem of sentiment analysis, techniques and methods used for the same.read more
Citations
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References
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Book
Opinion Mining and Sentiment Analysis
Bo Pang,Lillian Lee +1 more
TL;DR: This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems and focuses 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.
Proceedings ArticleDOI
Mining and summarizing customer reviews
Minqing Hu,Bing Liu +1 more
TL;DR: This research aims to mine and to summarize all the customer reviews of a product, and proposes several novel techniques to perform these tasks.
Journal ArticleDOI
Sentiment Analysis and Opinion Mining: A Survey
TL;DR: A survey which covers Opining Mining, Sentiment Analysis, techniques, tools and classification is presented which covers the polarity of extracted public opinions.
39. Opinion mining and sentiment analysis
Eric Breck,Claire Cardie +1 more
TL;DR: This paper introduced an idealised, end-to-end opinion analysis system and described its components, including constructing opinion lexica, performing sentiment analysis, and producing opinion summaries, which can be used for sentiment analysis.
Journal ArticleDOI
Experiments with SVM to classify opinions in different domains
TL;DR: This paper explores this new research area applying Support Vector Machines (SVM) for testing different domains of data sets and using several weighting schemes to prove the feasibility of the SVM for different domains.