Abstract
Twitter is one of the effective mediums to detect the feeling of a mass. Due to the increasing penetration of this kind of social services in the society, its relevance and the credibility are also increasing. In this article, we did an analysis of 16 different Indian Railways Zonal Regions and Zonal-wise passengers issues concerning traveling, using Latent Dirichlet Allocation (LDA). The results generated by the LDA shows that the major concerns of the passengers are the sanitation, security of women, rat and bad behavior by the other passengers. These results can be used to further improve the performance of the Indian Railways and in decision making.
Keywords: Indian Railways, Latent Dirichlet Allocation (LDA), Sentiment analysis, Topic mining
About this chapter
Cite this chapter as:
Vijay Singh, Mangey Ram, Bhasker Pant ;Identification of Zonal-Wise Passenger’s Issues in Indian Railways Using Latent Dirichlet Allocation (LDA): A Sentiment Analysis Approach On Tweets, Frontiers in Information Systems Mathematics Applied in Information Systems (2018) 2: 265. https://doi.org/10.2174/9781681087139118020015
DOI https://doi.org/10.2174/9781681087139118020015 |
Print ISSN 2589-3785 |
Publisher Name Bentham Science Publisher |
Online ISSN 2589-3793 |