Dynamic Behavior Analysis of Railway Passengers

Research Anthology on Strategies for Using Social Media as a Service and Tool in Business Pub Date : 1900-01-01 DOI:10.4018/978-1-5225-3176-0.CH007

M. M. Bala, V. Ravilla, Kamakshi Prasad, Akhil Dandamudi

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引用次数: 2

Abstract

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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铁路旅客动力行为分析

本章主要讨论利用twitter数据在正常和紧急情况下的铁路乘客动态行为。社交网络数据为各个领域提供了动态的、现实的数据。根据目前的章节主题，如果考虑铁路领域的twitter数据，那么它可以用于增强铁路服务。利用这些数据，讨论了一个综合的乘客推特数据建模框架，该框架包含了乘客对铁路提供的设施的意见。通过两个案例研究，阐述了动态数据提取、twitter文本内容准备和文本处理中寻找情感水平的主要问题;分别是乘客对铁路服务质量的情感分析和利用地理标记twitter数据识别乘客出行需求。情感分析根据乘客的旅行经历确定乘客对铁路提供的设施的正面或负面意见。

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Research Anthology on Strategies for Using Social Media as a Service and Tool in Business

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