Sentiment analysis and opinion mining

被引:136
作者
机构
[1] Liu, Bing
来源
Liu, Bing | 1600年 / Morgan and Claypool Publishers卷 / 05期
关键词
Affect; Attitude; Emotion; Evaluation; Mood; Natural language progressing; Opinion mining; Sentiment analysis; Social media; Text mining;
D O I
10.2200/S00416ED1V01Y201204HLT016
中图分类号
学科分类号
摘要
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Copyright © 2012 by Morgan & Claypool.
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页码:1 / 184
页数:183
相关论文
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  • [1] Ahmed A., Chen H., Salem A., Sentiment analysis in multiple languages: Feature selection for opinion classification in web forums, ACM Transactions on Information Systems (TOI S, 26, (2008)
  • [2] Muhammad A., Diab M.T., Korayem M., Subjectivity and sentiment analysis of modern standard Arabic in, Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics:shortpapers, (2011)
  • [3] Cem A., Wiebe J., Mihalcea R., Subjectivity word sense disambiguation, Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing (EMNLP-2009, (2009)
  • [4] Alm E., Cecilia ovesdotter, Affect in Text and Speech, (2008)
  • [5] Alina A., Bergler S., Mining wordnet for fuzzy sentiment: Sentiment tag extraction from wordnet glosses, Rroceedings of Conference of the European Chapter of the Association for Computational Linguistics (EAC) L-06, (2006)
  • [6] Alina A., Bergler S., When specialists and generalists work together: Overcoming domain dependence in sentiment tagging, Proceedings of the Annual Meeting of the Association for Computational Linguistics (AC)L-2008, (2008)
  • [7] David A., Zhu X., Latent dirichlet allocation with topic-in-set knowledge, Proceedings of NAAC L HLT, (2009)
  • [8] David A., Zhu X., Craven M., Incorporating domain knowledge into topic modeling via Dirichlet forest priors, Proceedings of ICML, (2009)
  • [9] Nikolay A., Ghose A., Ipeirotis P.G., Show me the money!: Deriving the pricing power of product features by mining consumer reviews, Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2007, (2007)
  • [10] Nicholas A., Benamara F., Yannick Mathieu Y., Distilling opinion in discourse: Preliminary study, Proceedings of the International Conference on Computational Linguistics (CO LING-2008): Companion Volume: Posters and Demonstrations, (2008)