Classification of Sentiment Analysis based on Adaptive Neuro Fuzzy Inference Model (ANFIS)
Ashwin Perti1, Amit Sinha2

1Mr. Ashwin Perti, Assistant Professor, Department of Computer Science and Engineering, Dr. A.P.J. Abdul Kalam Technical University, Lucknow (U.P), India.
2Prof. (Dr.) Amit Sinha, Professor and Head, Department of Information Technology, ABES Engineering College, Ghaziabad (U.P), India.
Manuscript received on 02 July 2022 | Revised Manuscript received on 05 July 2022 | Manuscript Accepted on 15 August 2022 | Manuscript published on 30 August 2022 | PP: 1-5 | Volume-11 Issue-9, August 2022 | Retrieval Number: 100.1/ijitee.G91850811922 | DOI: 10.35940/ijitee.G9185.0811922
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Abstract: With the growing demand of Social media and its various networks and with the emergence of virtual nature of Online Shopping users are not easily able to determine whether the quality of the product or service is good or worse. For this work there is no such specific model existed that can find similar or dissimilar products from the people posting tweets in the form of post, messages or hashtags using similar sort of textual content. Also the companies are giving their Product reviews, which contain the direct / Indirect feedback from the customers. The companies are also getting feedback from the social media in the form of tweets / post / blogs from the twitter in the form of text for the same product. So, to find the sentiments of an individual based on the product recommendations the work had been proposed. The reviews from various intelligent algorithm for sentimental classification based on Adaptive Neuro-Fuzzy Inference System were studied. The research work is based on the comparison of the other traditional based Sentiment Analysis methodology with the ANFIS. Therefore, we are able to identify the best method to be used for the reviews identification in the best possible method. 
Keywords: Adaptive Neuro-fuzzy Inference system (ANFIS), Sentiments Analysis, Machine Learning algorithms, Natural Language Processing (NLP), Online Shopping.
Scope of the Article: Machine Learning