Event participation recommendation in event-based social networks

Hao Ding, Chenguang Yu, Guangyu Li, Yong Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Event-based Social Networks (EBSN) have experienced rapid growth in recent years. Event participation recommendation is to recommend a list of users who are most likely to participate in a new event. Due to the nature of new event and severe data sparsity in EBSN, the traditional recommender systems do not work well for event participation recommendation. In this paper, we first conduct a study of Meetup users to understand the major factors impacting their event participation decisions. We then develop a sliding-window based machine-learning model that effectively combines user features from multiple channels to recommend users to new events. Through evaluation using the Meetup dataset, we demonstrate that our model can capture the short-term consistency of user preferences and outperforms the traditional popularitybased and nearest-neighbor based recommendation models. Our model is suitable for real-time recommendation on practical EBSN platforms.

Original languageEnglish (US)
Title of host publicationSocial Informatics - 8th International Conference, SocInfo 2016, Proceedings
EditorsEmma Spiro, Yong-Yeol Ahn
PublisherSpringer Verlag
Number of pages15
ISBN (Print)9783319478791
StatePublished - 2016
Event8th International Conference on Social Informatics, SocInfo 2016 - Bellevue, United States
Duration: Nov 11 2016Nov 14 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10046 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other8th International Conference on Social Informatics, SocInfo 2016
Country/TerritoryUnited States


  • Event participation recommendation
  • Event-based social networks
  • Social network analysis
  • Temporal recommendation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Event participation recommendation in event-based social networks'. Together they form a unique fingerprint.

Cite this