Open AccessOpinion Mining for Travel Route Recommendation using Social Media Networks (Twitter)
Author(s) -
R Velvizhi,
C. Rajabhushanam,
S Sri
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i3097.0789s319
Subject(s) - sentiment analysis , social media , computer science , syntax , set (abstract data type) , data science , process (computing) , path (computing) , microblogging , analytics , information retrieval , data mining , world wide web , artificial intelligence , programming language , operating system
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.