DocumentCode
3081735
Title
Detecting Dynamic and Static Geo-social Communities
Author
Lin, Fujian ; Renner, Renato
Author_Institution
Northrop Grumman Inf. Syst., McLean, VA, USA
fYear
2013
fDate
22-24 July 2013
Firstpage
134
Lastpage
135
Abstract
How communities form can depend on the geospatial location of people within a social network. Here, we investigated the implementation of the label propagation algorithm (LPA) and LabelRankT community detection algorithm in Gephi, a graph visualization tool. We researched extending these community detection algorithms to incorporate the geospatial distance between nodes in a network as a limiting factor for the automatic detection of community formation.
Keywords
data visualisation; social networking (online); LPA; LabelRankT community detection algorithm; community formation; dynamic geo-social communities; geospatial distance; geospatial location; graph visualization tool; label propagation algorithm; social network; static geo-social communities; Algorithm design and analysis; Attenuation; Communities; Geospatial analysis; Heuristic algorithms; Information systems; Social network services; Geo-Social Community Detection; Graph Algorithms; Label Propagation Algorithm; Social Network Analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing for Geospatial Research and Application (COM.Geo), 2013 Fourth International Conference on
Conference_Location
San Jose, CA
Type
conf
DOI
10.1109/COMGEO.2013.24
Filename
6602055
Link To Document