Please use this identifier to cite or link to this item: http://10.9.150.37:8080/dspace//handle/atmiyauni/1675
Title: Comparison of Different Hybrid Approaches Used for Sentiment Analysis: Survey
Authors: Chauhan, Mansi
Paneri, Devangi
Keywords: Machine learning
Data mining
Hybrid approach
Sentiment analysis
Issue Date: Apr-2021
Publisher: International Journal of Scientific Research & Engineering Trends
Citation: Chauhan, M., Paneri, D. (2021). Comparison of Different Hybrid Approaches Used for Sentiment Analysis: Survey. International Journal of Scientific Research & Engineering Trends, 7(2), 2395-566X.
Series/Report no.: 7;2
Abstract: In Today’s Technological Life Social media quiets a specious amount of Information. Social media has become a tremendous source of acquiring Users Opinions. It also helps to analyze how people, particularly consumers, feel about a particular topic, product or Idea. Among such opinions plays an important role in analyzing different business aspects. Sentiment analysis therefore becomes an effective way of Understanding public Opinions. Business Organizations can predict best Decision with Using Sentiment analysis. A lot of Research work has been done on Sentiment analysis in order to classify the opinions. Researchers have tested a variety of methods for automating the sentiment analysis process but very few Researchers are using Hybrid Approaches. This research paper shows the advantage of hybrid approaches to improve classification accuracy Compare to individuals. In proposed work a comparative study of the effectiveness of hybrid approaches was used for Sentiment analysis. Empirical results indicate that the hybrid approaches outperform compare to this individuals Classifiers.
URI: http://10.9.150.37:8080/dspace//handle/atmiyauni/1675
ISSN: 2395-566X
Appears in Collections:01. Journal Articles

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