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Event Detection Using Twitter Platform

  • Anuradha Goswami
  • Ajey KumarEmail author
Chapter
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 21)

Abstract

Online Social Network (OSN) has evolved through a radical transformation in the way user communicate with each other in the Web 2.0 environment. User communicate over OSN through a connected network structure, forming a group of individuals who interacts among themselves. Interaction among users, within a community or inter-community, facilitates in the formation and exchange of huge User-Generated Content (UGC) across the OSN platforms. UGC is an important source for researchers to extract relevant insights related to events of significance e.g. earthquake, product review, emerging topics, etc. In this chapter, a comprehensive survey of event detection techniques for OSN is done. First, the types of OSN based on information flow (service oriented, sharing services, Social Network Sharing News, Location Based Social Network and community building Social networks) and then the various categories of events (natural or manmade disaster events, public opinion events & emerging events) are studied. Second, events were categorized based on four dimensions—thematic, temporal, spatial and network structure. An extensive survey of dimension-wise event detection techniques is carried out and the research gaps are identified. Third, Twitter platform was taken as a case study due to its popularity among users as well as researchers. An in-depth survey of event detection techniques with respect to different dimensions applicable to Twitter data for disaster event management, detection of emerging events and prediction of emerging events is performed and respective research challenges are enlisted. Finally, an exclusive study is conducted for Twitter platform based data collection and event detection & analysis tools. The suggested open challenges will give researchers/readers ample scope to work upon.

Keywords

Web 2.0 Online social networks Twitter Event detection Disaster events Emerging trends Public opinion events Data collection tools Event detection tools 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Symbiosis Centre for Information Technology (SCIT), Symbiosis International (Deemed University) (SIU)PuneIndia

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