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
Related Journals
Related Books
Computational Intelligence For Data Analysis
Machine Learning and Its Application: A Quick Guide for Beginners
Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare
A First Course in Artificial Intelligence
Artificial Intelligence: Models, Algorithms and Applications
Advanced Computing Techniques: Implementation, Informatics and Emerging Technologies
Handbook of Mobile Application Development: A Guide to Selecting the Right Engineering and Quality Features
Ad Hoc and Sensor Wireless Networks: Architectures, Algorithms and Protocols
Applications of Modern High Performance Networks
Arduino Meets Matlab: Interfacing, Programs and Simulink