TY - JOUR
T1 - Understanding community dynamics in online social networks
T2 - A multidisciplinary review
AU - Sundaram, Hari
AU - Lin, Yu Ru
AU - De Choudhury, Munmun
AU - Kelliher, Aisling
N1 - Funding Information:
Aisling Kelliher ([email protected]) is an assistant professor in media communication systems and theory in the School of Arts, Media, and Engineering at Arizona State University. Her primary research interests include rich-media storytelling, narrative computation, social network analysis, media summarization, and experiential design. Her work has been published in the Journal of Science Education and Technology, SIGCHI, ISEA, CIKM, ICWSM, and WWW, and has been exhibited at leading national cultural events including SIGGRAPH and the Boston Cyberarts Festival. Her research is supported by grants from the MacArthur Foundation, National Science Foundation Integrative Graduate Education and Research Traineeship (IGERT) and Sustainable Futures IGERT Programs, Discovery Research K-12, and CreativeIT programs.
PY - 2012/3
Y1 - 2012/3
N2 - Social network systems are significant scaffolds for political, economic, and sociocultural change. This is in part due to the widespread availability of sophisticated network technologies and the concurrent emergence of rich media Web sites. Social network sites provide new opportunities for social-technological research. Since we can inexpensively collect electronic records (over extended periods) of social data spanning diverse populations, it is now possible to study social processes on a scale of tens of million individuals. To understand the large-scale dynamics of interpersonal interaction and its outcome, this article links the perspectives in the humanities for analysis of social networks to recent developments in data intensive computational approaches. With special emphasis on social communities mediated by network technologies, we review the historical research arc of community analysis as well as methods applicable to community discovery in social media.
AB - Social network systems are significant scaffolds for political, economic, and sociocultural change. This is in part due to the widespread availability of sophisticated network technologies and the concurrent emergence of rich media Web sites. Social network sites provide new opportunities for social-technological research. Since we can inexpensively collect electronic records (over extended periods) of social data spanning diverse populations, it is now possible to study social processes on a scale of tens of million individuals. To understand the large-scale dynamics of interpersonal interaction and its outcome, this article links the perspectives in the humanities for analysis of social networks to recent developments in data intensive computational approaches. With special emphasis on social communities mediated by network technologies, we review the historical research arc of community analysis as well as methods applicable to community discovery in social media.
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U2 - 10.1109/MSP.2011.943583
DO - 10.1109/MSP.2011.943583
M3 - Review article
AN - SCOPUS:85032751909
SN - 1053-5888
VL - 29
SP - 33
EP - 40
JO - IEEE Signal Processing Magazine
JF - IEEE Signal Processing Magazine
IS - 2
M1 - 6153141
ER -