{"_id":"Z6mojKFbwYmZL7K3K","bibbaseid":"alvari-hajibagheri-sukthankar-communitydetectionindynamicsocialnetworksagametheoreticapproach-2014","author_short":["Alvari, H.","Hajibagheri, A.","Sukthankar, G."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","title":"Community detection in dynamic social networks: A game-theoretic approach","shorttitle":"Community detection in dynamic social networks","doi":"10.1109/ASONAM.2014.6921567","abstract":"Most real-world social networks are inherently dynamic and composed of communities that are constantly changing in membership. As a result, recent years have witnessed increased attention toward the challenging problem of detecting evolving communities. This paper presents a game-theoretic approach for community detection in dynamic social networks in which each node is treated as a rational agent who periodically chooses from a set of predefined actions in order to maximize its utility function. The community structure of a snapshot emerges after the game reaches Nash equilibrium; the partitions and agent information are then transferred to the next snapshot. An evaluation of our method on two real world dynamic datasets (AS-Internet Routers Graph and AS-Oregon Graph) demonstrates that we are able to report more stable and accurate communities over time compared to the benchmark methods.","booktitle":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","author":[{"propositions":[],"lastnames":["Alvari"],"firstnames":["H."],"suffixes":[]},{"propositions":[],"lastnames":["Hajibagheri"],"firstnames":["A."],"suffixes":[]},{"propositions":[],"lastnames":["Sukthankar"],"firstnames":["G."],"suffixes":[]}],"month":"August","year":"2014","pages":"101–107","bibtex":"@inproceedings{alvari_community_2014,\n\ttitle = {Community detection in dynamic social networks: {A} game-theoretic approach},\n\tshorttitle = {Community detection in dynamic social networks},\n\tdoi = {10.1109/ASONAM.2014.6921567},\n\tabstract = {Most real-world social networks are inherently dynamic and composed of communities that are constantly changing in membership. As a result, recent years have witnessed increased attention toward the challenging problem of detecting evolving communities. This paper presents a game-theoretic approach for community detection in dynamic social networks in which each node is treated as a rational agent who periodically chooses from a set of predefined actions in order to maximize its utility function. The community structure of a snapshot emerges after the game reaches Nash equilibrium; the partitions and agent information are then transferred to the next snapshot. An evaluation of our method on two real world dynamic datasets (AS-Internet Routers Graph and AS-Oregon Graph) demonstrates that we are able to report more stable and accurate communities over time compared to the benchmark methods.},\n\tbooktitle = {2014 {IEEE}/{ACM} {International} {Conference} on {Advances} in {Social} {Networks} {Analysis} and {Mining} ({ASONAM} 2014)},\n\tauthor = {Alvari, H. and Hajibagheri, A. and Sukthankar, G.},\n\tmonth = aug,\n\tyear = {2014},\n\tpages = {101--107},\n}\n\n","author_short":["Alvari, H.","Hajibagheri, A.","Sukthankar, G."],"key":"alvari_community_2014","id":"alvari_community_2014","bibbaseid":"alvari-hajibagheri-sukthankar-communitydetectionindynamicsocialnetworksagametheoreticapproach-2014","role":"author","urls":{},"metadata":{"authorlinks":{}},"html":""},"bibtype":"inproceedings","biburl":"https://bibbase.org/zotero/wybert","dataSources":["TJkbwzD8s2wCxBy6Y"],"keywords":[],"search_terms":["community","detection","dynamic","social","networks","game","theoretic","approach","alvari","hajibagheri","sukthankar"],"title":"Community detection in dynamic social networks: A game-theoretic approach","year":2014}