2012 EventbasedSocialNetworksLinking

• (Liu et al., 2012) ⇒ Xingjie Liu, Qi He, Yuanyuan Tian, Wang-Chien Lee, John McPherson, and Jiawei Han. (2012). “Event-based Social Networks: Linking the Online and Offline Social Worlds.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2012). ISBN:978-1-4503-1462-6 doi:10.1145/2339530.2339693

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222012%22+Event-based+Social+Networks%3A+Linking+the+Online+and+Offline+Social+Worlds
• http://dl.acm.org/citation.cfm?id=2339530.2339693&preflayout=flat#citedby

Quotes

Author Keywords

• Event based social networks; heterogeneous network; information networks; online and offline social behaviors; social event recommendation; social network analysis

Abstract

Newly emerged event-based online social services, such as Meetup and Plancast, have experienced increased popularity and rapid growth. From these services, we observed a new type of social network - event-based social network (EBSN). An EBSN does not only contain online social interactions as in other conventional online social networks, but also includes valuable offline social interactions captured in offline activities. By analyzing real data collected from Meetup, we investigated EBSN properties and discovered many unique and interesting characteristics, such as heavy-tailed degree distributions and strong locality of social interactions.

We subsequently studied the heterogeneous nature (co-existence of both online and offline social interactions) of EBSNs on two challenging problems: community detection and information flow. We found that communities detected in EBSNs are more cohesive than those in other types of social networks (e.g. location-based social networks). In the context of information flow, we studied the event recommendation problem. By experimenting various information diffusion patterns, we found that a community-based diffusion model that takes into account of both online and offline interactions provides the best prediction power.

This paper is the first research to study EBSNs at scale and paves the way for future studies on this new type of social network. A sample dataset of this study can be downloaded from http://www.largenetwork.org/ebsn.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2012 EventbasedSocialNetworksLinking	Qi He Wang-Chien Lee Yuanyuan Tian Xingjie Liu John McPherson Jiawei Han			Event-based Social Networks: Linking the Online and Offline Social Worlds				10.1145/2339530.2339693		2012