TY - JOUR
T1 - Inferring social status and rich club effects in enterprise communication networks
AU - Dong, Yuxiao
AU - Tang, Jie
AU - Chawla, Nitesh V.
AU - Lou, Tiancheng
AU - Yang, Yang
AU - Wang, Bai
N1 - Publisher Copyright:
© 2015 Dong et al.
PY - 2015/3/30
Y1 - 2015/3/30
N2 - Social status, defined as the relative rank or position that an individual holds in a social hierarchy, is known to be among the most important motivating forces in social behaviors. In this paper, we consider the notion of status from the perspective of a position or title held by a person in an enterprise. We study the intersection of social status and social networks in an enterprise.We study whether enterprise communication logs can help reveal how social interactions and individual status manifest themselves in social networks. To that end, we use two enterprise datasets with three communication channels - voice call, short message, and email - to demonstrate the social-behavioral differences among individuals with different status. We have several interesting findings and based on these findings we also develop a model to predict social status. On the individual level, high-status individuals are more likely to be spanned as structural holes by linking to people in parts of the enterprise networks that are otherwise not well connected to one another. On the community level, the principle of homophily, social balance and clique theory generally indicate a "rich club" maintained by high-status individuals, in the sense that this community is much more connected, balanced and dense. Our model can predict social status of individuals with 93% accuracy.
AB - Social status, defined as the relative rank or position that an individual holds in a social hierarchy, is known to be among the most important motivating forces in social behaviors. In this paper, we consider the notion of status from the perspective of a position or title held by a person in an enterprise. We study the intersection of social status and social networks in an enterprise.We study whether enterprise communication logs can help reveal how social interactions and individual status manifest themselves in social networks. To that end, we use two enterprise datasets with three communication channels - voice call, short message, and email - to demonstrate the social-behavioral differences among individuals with different status. We have several interesting findings and based on these findings we also develop a model to predict social status. On the individual level, high-status individuals are more likely to be spanned as structural holes by linking to people in parts of the enterprise networks that are otherwise not well connected to one another. On the community level, the principle of homophily, social balance and clique theory generally indicate a "rich club" maintained by high-status individuals, in the sense that this community is much more connected, balanced and dense. Our model can predict social status of individuals with 93% accuracy.
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U2 - 10.1371/journal.pone.0119446
DO - 10.1371/journal.pone.0119446
M3 - Article
C2 - 25822343
AN - SCOPUS:84926644887
SN - 1932-6203
VL - 10
JO - PloS one
JF - PloS one
IS - 3
M1 - e0119446
ER -