Opinion Mining for Travel Route Recommendation using Social Media Networks (Twitter)
C. Nalini1, T. Poovizhi2

1Dr. C. Nalini, Department of Computer Science Engineering, Bharath Institute of Higher Education and Research Chennai (Tamil Nadu), India.
2Poovizhi.T, Department of Computer Science Engineering, Bharath Insitute of  Higher Education and Research, Chennai (Tamil Nadu), India.

Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 1238-1242 | Volume-8 Issue-5, June 2019 | Retrieval Number: E7588068519/19©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: 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: Data Mining