Evaluation of Sentiment Data using Classifier Model in Rapid Miner Tool

B, Devipriya and Y, Kalpana (2019) Evaluation of Sentiment Data using Classifier Model in Rapid Miner Tool. International Journal of Engineering and Advanced Technology, 9 (1). pp. 2966-2972. ISSN 22498958

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Abstract

Evaluation of Sentiment Data using Classifier Model in Rapid Miner Tool Department of Information Technology, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, India. Devipriya B Dr Kalpana Y Department of Information Technology, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, India.

Evaluation of internet and the usage of internet as websites which is for penetrating to gain a specific requirements, like group communication as social networks (such as face book, twitter,etc.,) ,blogs for opinions, online portals (such as iGoogle, MSN) for communication, experience as reviews, suggestions as opinions, combination of reviews and opinions as recommendations, ratings and feedbacks which is identified and elevating in almost all the field now-a-days. The writers of online portal, review, opinion and recommendation in any social media take measures as beneficial factor for the improvement of businesses, organization, governments and mostly individuals. When this content boost up the study of content and the need of data mining, text mining techniques and sentiment analysis is inescapable. Natural language processing and text analysis techniques are used in sentiment analysis to recognize and extract information from the text [1]. This paper provides a result of sentiment analysis with the intellectual tool named Rapid Miner to show the sentiment comments about the contents in the online traders.
10 30 2019 2966 2972 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.A1323.109119 https://www.ijeat.org/portfolio-item/a1323109119/ https://www.ijeat.org/wp-content/uploads/papers/v9i1/A1323109119.pdf

Item Type: Article
Subjects: Information Technology > Data Management
Divisions: Information Technology
Depositing User: Mr IR Admin
Date Deposited: 02 Oct 2024 10:37
Last Modified: 02 Oct 2024 10:37
URI: https://ir.vistas.ac.in/id/eprint/8160

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