A Survey on Social Digital Data-Based Sentiment Mining Techniques and Feature
  IJCTT-book-cover
 		          
 
© 2021 by IJCTT Journal
Volume-69 Issue-4
Year of Publication : 2021
Authors : Rajesh Sisodiya, Dr. Praveen Kumar Mannepalli
DOI :  10.14445/22312803/IJCTT-V69I4P107

How to Cite?

Rajesh Sisodiya, Dr. Praveen Kumar Mannepalli, "A Survey on Social Digital Data-Based Sentiment Mining Techniques and Feature," International Journal of Computer Trends and Technology, vol. 69, no. 4, pp. 34-38, 2021. Crossref, https://doi.org/10.14445/22312803/IJCTT-V69I4P107

Abstract
Sentiment mining plays a very important role in business to understand the opinion of customers to improve the Customer of the products also depends on the opinion of others who have bought the products already. Reviews or feedback becomes the deciding factor for buy or sells a product. This paper has focused on elaborating the user rating behavior for a particular kind of service, product, news. Techniques developed by various researchers are discussed with their implementation dataset and outcomes. Some digital features are also detailed, which play an important role in increasing the accuracy for the prediction of sentiment class. Types of sentiment analysis and mining were also detailed. Paper has summarized evaluation parameter values of the sentiment data analysis for comparing techniques

Keywords
Data mining, Online Social content, Sentiment analysis, Text Clustering.

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