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How online social network affects offline events: A case study on douban

  • Junwei Han*
  • , Jianwei Niu
  • , Alvin Chin
  • , Wei Wang
  • , Chao Tong
  • , Xia Wang
  • *Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

Social networking sites (SNS) such as Facebook and Twitter are becoming popular forms for finding, promoting and attending offline events and activities. Much work has looked into characterizing these social networks and their user behavior. With the emergence of event and activity-based applications such as Facebook Events, LinkedIn Events, Xinghui, Zaizher, and Douban, it is easier to connect with other people online and meet them offline. However, few have looked into analyzing these offline events and activities that are shared online. This paper seeks to gain insights into the user behavior around people attending offline events which are promoted online. By studying the events in Douban, we present results around the event properties, user behavior of participants and wishers to an event, and social influence to an event. We show that event distribution by participants and wishers follow the typical power-law distribution; most users attend or like short events that last several days or regular events that last less than 3 months; participants attend an event within one day after the publish time; and that there is an exponential relationship between follow probability and number of common events attended between two users and a linear relationship for common events interested in. These findings provide a better understanding on how SNS could affect user behavior in attending events, and provide guidelines on how to improve the design of event-based applications.

Conference

Conference9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012 and 9th IEEE International Conference on Autonomic and Trusted Computing, ATC 2012
Country/TerritoryJapan
CityFukuoka
Period4/09/127/09/12

Keywords

  • Event
  • Offline
  • Online
  • Social network
  • User behavior

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