Dynamic Behavior Analysis of Railway Passengers

Dynamic Behavior Analysis of Railway Passengers

Myneni Madhu Bala (Institute of Aeronautical Engineering, India), Venkata Krishnaiah Ravilla (Institute of Aeronautical Engineering, India), Kamakshi Prasad V (JNTUH, India) and Akhil Dandamudi (NIIT University, India)
Copyright: © 2018 |Pages: 26
DOI: 10.4018/978-1-5225-3176-0.ch007
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This chapter discusses mainly on dynamic behavior of railway passengers by using twitter data during regular and emergency situations. Social network data is providing dynamic and realistic data in various fields. As per the current chapter theme, if the twitter data of railway field is considered then it can be used for enhancement of railway services. Using this data, a comprehensive framework for modeling passenger tweets data which incorporates passenger opinions towards facilities provided by railways are discussed. The major issues elaborated regarding dynamic data extraction, preparation of twitter text content and text processing for finding sentiment levels is presented by two case studies; which are sentiment analysis on passenger's opinions about quality of railway services and identification of passenger travel demands using geotagged twitter data. The sentiment analysis ascertains passenger opinions towards facilities provided by railways either positive or negative based on their journey experiences.
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An explanatory study to investigate the use of text mining and sentiment analysis for railway services enhancement on relevant content extracted from twitter for exploring different applications. Due to the complexity of information extraction from social media for focused tasks like passenger complaints, trips planning, understanding passenger behavior at city visits and sentiment analysis on events. At present, Indian railways' current practice on performance survey is relying on multiple sources such as SMS, web feedback, and twitter hashtags.

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