Dynamic Behavior Analysis of Railway Passengers

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.