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Cognitive Science and Artificial Intelligence pp 79–89Cite as

Feature Based Opinion Mining and Sentiment Analysis Using Fuzzy Logic

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Abstract

This paper discusses a new model towards opinion mining and sentiment analysis of the text reviews posted in social media sites which are mostly in unstructured format. In recent years, web forums and social media has become an excellent platform to express or share opinions in the form of text about any product or any interested topic. These opinions are used for making decisions to choose a product or any entity. Opinion mining and sentiment analysis are related in a sense that opining mining deals with analyzing and summarizing expressed opinions whereas sentiment analysis classifies opinionated text into positive and negative. Feature extraction is a crucial problem in sentiment analysis. Model proposed in the paper utilizes machine learning techniques and fuzzy approach for opinion mining and classification of sentiment on textual reviews. The goal is to automate the process of mining attitudes, opinions and hidden emotions from text.

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Author information

Authors and Affiliations

  1. Department of CSE, JNTUA, Anantapuramu, India

    B. Vamshi Krishna & A. P. Siva Kumar

  2. L&T Technology Services, Bangalore, India

    Ajeet Kumar Pandey

Authors
  1. B. Vamshi Krishna
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  2. Ajeet Kumar Pandey
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  3. A. P. Siva Kumar
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Correspondence to B. Vamshi Krishna .

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Vamshi Krishna, B., Pandey, A.K., Siva Kumar, A.P. (2018). Feature Based Opinion Mining and Sentiment Analysis Using Fuzzy Logic. In: Cognitive Science and Artificial Intelligence. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-10-6698-6_8

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  • DOI: https://doi.org/10.1007/978-981-10-6698-6_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6697-9

  • Online ISBN: 978-981-10-6698-6

  • eBook Packages: EngineeringEngineering (R0)

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