TY - GEN
T1 - On a triadic approach to connect microstructural properties to social macrostructural patterns
AU - Hu, Yuxi
AU - Doroud, Mina
AU - Felix Wu, S.
PY - 2012
Y1 - 2012
N2 - Social macrostructures, such as structural balance, ranked clusters and transitivity, are of great importance on account of their abilities to reflect the underlying social psychological processes about the formation and evolution of relationships among people. Here we present a detailed study on examining the existence and evolution of social macrostructures in an empirical online social network, and exploring how they can be explained by network microstructural properties, i.e. nodal indegree and outdegree and dyadic feature. We establish the micro-macro linkage by analyzing the network triadic patterns. Based on a novel clustering coefficient based network sampling approach, we show that the distribution of observed triad census in our data is low dimensional and can be greatly explained by network dyadic properties. In a time series analysis, we observe that our network exhibits strong tendencies towards balanced, transitive and clustered social macrostructure given the nodal and dyadic characteristics. Our findings supplement the studies on structural properties of online social network by providing more insights on the relation between network macrostructures and the microlevel social processes that result in them. And they form the basis to understand better how online social media systems change the information and communication fabric of our society.
AB - Social macrostructures, such as structural balance, ranked clusters and transitivity, are of great importance on account of their abilities to reflect the underlying social psychological processes about the formation and evolution of relationships among people. Here we present a detailed study on examining the existence and evolution of social macrostructures in an empirical online social network, and exploring how they can be explained by network microstructural properties, i.e. nodal indegree and outdegree and dyadic feature. We establish the micro-macro linkage by analyzing the network triadic patterns. Based on a novel clustering coefficient based network sampling approach, we show that the distribution of observed triad census in our data is low dimensional and can be greatly explained by network dyadic properties. In a time series analysis, we observe that our network exhibits strong tendencies towards balanced, transitive and clustered social macrostructure given the nodal and dyadic characteristics. Our findings supplement the studies on structural properties of online social network by providing more insights on the relation between network macrostructures and the microlevel social processes that result in them. And they form the basis to understand better how online social media systems change the information and communication fabric of our society.
UR - https://www.scopus.com/pages/publications/84874283784
UR - https://www.scopus.com/pages/publications/84874283784#tab=citedBy
U2 - 10.1109/ASONAM.2012.65
DO - 10.1109/ASONAM.2012.65
M3 - Conference contribution
AN - SCOPUS:84874283784
SN - 9780769547992
T3 - Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
SP - 353
EP - 359
BT - Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
T2 - 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Y2 - 26 August 2012 through 29 August 2012
ER -