Information flow in social groups Export

@article{citeulike:311565, abstract = {We present a study of information flow that takes into account the observation that an item relevant to one person is more likely to be of interest to individuals in the same social circle than those outside of it. This is due to the fact that the similarity of node attributes in social networks decreases as a function of the graph distance. An epidemic model on a scale-free network with this property has a finite threshold, implying that the spread of information is limited. We tested our predictions by measuring the spread of messages in an organization and also by numerical experiments that take into consideration the organizational distance among individuals.}, author = {Wu, Fang and Huberman, Bernardo A. and Adamic, Lada A. and Tyler, Joshua R.}, citeulike-article-id = {311565}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.physa.2004.01.030}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S0378437104000548}, citeulike-linkout-2 = {http://www.sciencedirect.com/science/article/B6TVG-4BNMC3W-2/2/647d610316bf69d693bc28ba370ae5af}, citeulike-linkout-3 = {http://arxiv.org/pdf/cond-mat/0305305}, day = {1}, doi = {10.1016/j.physa.2004.01.030}, journal = {Physica A: Statistical and Theoretical Physics}, keywords = {adamic, diffusion, huberman, information-flow, social-dynamics, socialnetworks}, month = {June}, number = {1-2}, pages = {327--335}, posted-at = {2008-12-17 21:17:35}, priority = {2}, title = {Information flow in social groups}, url = {http://dx.doi.org/10.1016/j.physa.2004.01.030}, volume = {337}, year = {2004} }

TY - JOUR ID - citeulike:311565 L3 - citeulike-article-id:311565 N2 - We present a study of information flow that takes into account the observation that an item relevant to one person is more likely to be of interest to individuals in the same social circle than those outside of it. This is due to the fact that the similarity of node attributes in social networks decreases as a function of the graph distance. An epidemic model on a scale-free network with this property has a finite threshold, implying that the spread of information is limited. We tested our predictions by measuring the spread of messages in an organization and also by numerical experiments that take into consideration the organizational distance among individuals. IS - 1-2 JF - Physica A: Statistical and Theoretical Physics EP - 335 TI - Information flow in social groups VL - 337 SP - 327 KW - adamic KW - diffusion KW - huberman KW - information-flow KW - social-dynamics KW - socialnetworks AU - Wu, Fang AU - Huberman, Bernardo AU - Adamic, Lada AU - Tyler, Joshua PY - 2004/06/01/ UR - http://dx.doi.org/10.1016/j.physa.2004.01.030 ER -