Title :
Influence of the Dynamic Social Network Timeframe Type and Size on the Group Evolution Discovery
Author :
Saganowski, Stanislaw ; Brodka, Piotr ; Kazienko, P.
Author_Institution :
Inst. of Inf., Wroclaw Univ. of Technol., Wroclaw, Poland
Abstract :
New technologies allow to store vast amount of data about users interaction. From those data the social network can be created. Additionally, because usually also time and dates of this activities are stored, the dynamic of such network can be analyzed by splitting it into many timeframes representing the state of the network during specific period of time. One of the most interesting issue is group evolution over time. To track group evolution the GED method can be used. However, choice of the timeframe type and length might have great influence on the method results. Therefore, in this paper, the influence of timeframe type as well as timeframe length on the GED method results is extensively analyzed.
Keywords :
group theory; social aspects of automation; GED method; dynamic social network timeframe type; group evolution discovery; timeframe length; users interaction; Communities; Conferences; Data mining; Merging; Position measurement; Social network services; USA Councils; GED; group dynamics; group evolution; groups in social networks; social network; social network analysis; timeframe type; user position;
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-2497-7
DOI :
10.1109/ASONAM.2012.113
