Lifespan and popularity measurement of online content on social networks

Beiming Sun, Vincent To Yee Ng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

7 Citations (Scopus)

Abstract

With rapid development and increased popularity of social networks, more interests have been made in obtaining information from such social networking websites. Analysis on the popularity of online contents is one of the hottest interests which has triggered intensive research. Our research focuses on measuring the popularity of online posts within specified topics, such as "drug abuse", as it can be used to detect the crime and discover potential drug abusers. We measure the lifespan and the popularity of drug related posts in order to know the level of influence they made. Identifying popular posts online can help us reveal the trend, and also detect the latent danger and may prevent future crime. In this paper, the Comment Arrival Model is proposed to identify the lifespan and the comment frequency pattern of posts, which are considered the main factors to define post popularity. And we present 4 general models to measure the popularity of posts which can be applied in different social network platforms. We also did experiments and evaluated the performance of models in two popular social networks in Hong Kong, HK Discussion and Twitter.
Original languageEnglish
Title of host publicationProceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011
Pages379-383
Number of pages5
DOIs
Publication statusPublished - 22 Sep 2011
Event2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 - Beijing, China
Duration: 10 Jul 201112 Jul 2011

Conference

Conference2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011
Country/TerritoryChina
CityBeijing
Period10/07/1112/07/11

Keywords

  • crime detection
  • data mining
  • popularity measure
  • social network analysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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