Unusual Social Event Detection by Analyzing Call Data Records

  • V. P. Sumathi
  • K. Kousalya
  • V. Vanitha
  • N. Suganthi
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)


The availability of call data records provides an opportunity to identify unusual social events occurring in the society in an effective manner. The visitors participating in the events are the most important stakeholders for event organizers to improve their success rate. Visitors global positioning system (GPS) enabled device provides spatial data that are used to identify the visitors’ presence during event time. Mobile call data records (CDR) represent a real spatial data source to detect occupied visitors, but provide less accuracy in terms of time and space resolution. Using spatial data, it is possible to detect unusual events. In this paper, the method for detecting unusual social events in various locations is proposed. The CDRs are used to detect new visitors who participated in the event and total number of visitors participated is computed for free-to-view social event. The information extracted from preprocessed CDRs are utilized to identify new visitors and to compute total visitors present in an event place effectively. The tower-wise visitor’s details and CDR details provide information about the visitors’ movement as well as CDRs distribution pattern during the event time. The experiment is conducted on real CDRs provided by a telecommunication service provider (TSP) servicing in a larger city. Results show that the proposed method provides accurate identification visitors involved in unusual social events compared to the state-of-the art methods.


Social event analysis CDR analysis Free-to-view event Participant crowd detection Event analysis 



I thank Indian Academy of Science (IAS) for having given me an opportunity to take up research under Summer Research Fellowship Programme at Indian Institute of Science (IISc), Bengaluru. It has provided me valuable suggestions and data set for doing the present work in Super Computer Research Centre in IISc.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • V. P. Sumathi
    • 1
  • K. Kousalya
    • 2
  • V. Vanitha
    • 1
  • N. Suganthi
    • 1
  1. 1.Department of Computer Science and EngineeringKumaraguru College of TechnologyCoimbatoreIndia
  2. 2.Department of Computer Science and EngineeringKongu Engineering CollegePerunduraiIndia

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