User association analysis of locales on location based social networks

Josh Jia Ching Ying*, Wang Chien Lee, Mao Ye, Ching Yu Chen, S. Tseng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

In recent years, location-based social networks (LBSNs) have received high attention. While this new breed of social networks is nascent, there is no large-scale analysis conducted to investigate the associations among users in locales of the network. In this paper, we propose four locale based metrics, including Locale Clustering Coefficient, Inward Locale Transitivity, Locale Assortativity Coefficient, and Locale Assortability Coefficient to make association analysis on EveryTrail, a popular LBSN specialized on sharing trips. Based on the analysis result, we observe that people who share more trajectories will get more attention by other users, and people who are popular will connect to the people who are also popular.

Original languageEnglish
Title of host publication3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2011 - Held in Conjunction with the 19th ACM SIGSPATIAL GIS 2011
DOIs
StatePublished - 2011
Event3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2011 - Held in Conjunction with the 19th ACM SIGSPATIAL GIS 2011 - Chicago, IL, United States
Duration: 1 Nov 20111 Nov 2011

Publication series

Name3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2011 - Held in Conjunction with the 19th ACM SIGSPATIAL GIS 2011

Conference

Conference3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2011 - Held in Conjunction with the 19th ACM SIGSPATIAL GIS 2011
Country/TerritoryUnited States
CityChicago, IL
Period1/11/111/11/11

Keywords

  • assortativity coefficient
  • clustering coefficient
  • inward transitivity
  • locale based metrics
  • social network analysis

Fingerprint

Dive into the research topics of 'User association analysis of locales on location based social networks'. Together they form a unique fingerprint.

Cite this