Opinion Mining for Travel Route Recommendation using Social Media Networks (Twitter)
R. Velvizhi1, C. Rajabhushanam2, S.R. Sri Vidhya3
1R. Velvizhi, Department of Computer Science and Engineering, Bharath Institute of Higher education and research, Chennai, India.
2C. Rajabhushanam, Department of Computer Science and Engineering, Bharath Institute of Higher education and research, Chennai, India.
3S.R. Sri Vidhya, Department of Computer Science and Engineering, Bharath Institute of Higher education and research, Chennai, India
Manuscript received on 04 July 2019 | Revised Manuscript received on 17 July 2019 | Manuscript Published on 23 August 2019 | PP: 508-512 | Volume-8 Issue-9S3 August 2019 | Retrieval Number: I30970789S319/2019©BEIESP | DOI: 10.35940/ijitee.I3097.0789S319
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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: Most of the organizations use text analytics to uncover purposeful information from an unstructured text as a result of considering the linguistic communication process techniques area unit extremely difficult. They typically cause several issues because of the inconsistency in syntax and linguistics. Sentiment analysis based on the opinion of the users. On twitter, many people post about their experience on the traffic routes. This project discusses the prediction of text mining analysis. On that post collecting from the data set and we find out which path is the best path for the travellers and waiting for commuters. In this project we discuss the traffic mining tweets using the keywords predicting the positive and negative comment on the Twitter. Experimentation involves discussion and comparison of ensemble classifiers over tagged tweets. Finally, it will be finding the best accuracy.
Keywords: Sentiment analysis, Traffic, Twitter data, Route Recommendation.
Scope of the Article: Web Mining