Understanding User Migration Patterns in Social Media

Shamanth Kumar, Reza Zafarani, Huan Liu

Research output: Chapter in Book/Entry/PoemConference contribution

27 Scopus citations


The incredible growth of the social web over the last decade has ushered in a flurry of new social media sites. On one hand, users have an inordinate number of choices; on the other hand, users are constrained by limited time and resources and have to choose sites in order to remain social and active. Hence, dynamic social media entails user migration, a well studied phenomenon in fields such as sociology and psychology. Users are valuable assets for social media sites as they help contribute to the growth of a site and generate revenue by increased traffic. We are intrigued to know if social media user migration can be studied, and what migration patterns are. In particular, we investigate whether people migrate, and if they do, how they migrate. We formalize site and attention migration to help identify the migration between popular social media sites and determine clear patterns of migration between sites. This work suggests a feasible way to study migration patterns in social media. The discovered patterns can help understand social media sites and gauge their popularity to improve business intelligence and revenue generation through the retention of users.

Original languageEnglish (US)
Title of host publicationProceedings of the 25th AAAI Conference on Artificial Intelligence, AAAI 2011
PublisherAAAI Press
Number of pages6
ISBN (Electronic)9781577355083
StatePublished - Aug 11 2011
Externally publishedYes
Event25th AAAI Conference on Artificial Intelligence, AAAI 2011 - San Francisco, United States
Duration: Aug 7 2011Aug 11 2011

Publication series

NameProceedings of the 25th AAAI Conference on Artificial Intelligence, AAAI 2011


Conference25th AAAI Conference on Artificial Intelligence, AAAI 2011
Country/TerritoryUnited States
CitySan Francisco

ASJC Scopus subject areas

  • Artificial Intelligence


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