Sentiment Analysis Using Naïve Bayes Classifier
Kavya Suppala1, Narasinga Rao2
1Kavya Suppala, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India.
2Narasinga Rao, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 264-269 | Volume-8 Issue-8, June 2019 | Retrieval Number: H6330068819/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Twitteris a web service and social communication platform which allow users to address their tweets in different domains. Public can easily and efficiently explicit their perspectives and ideas on a wide variety of cluster on topics via social networking websites. As online data is abundant through different platforms like social networks, twitter, Facebook, etc… Analysing the data is of paramount importance in drawing inference from the data. Hence, in our research, we try to perform sentiment analysis on twitter data by using a Naive Bayesian algorithm. By using our model, we can measure the customers opinions and perceptions and can be enhanced to any desired level depending on the data gathered from on line resources.
Keyword: Twitter data, Machine learning, and naïveBayes classifier.
Scope of the Article: Predictive Analysis