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Gender-based Opportunity Structures in an Activity-based Online Social Network

Mon, August 22, 10:30am to 12:10pm, TBA

Abstract

People adjust not only their opinions, but also their behaviors based on both direct and indirect social interaction. Questions about social influence are particularly salient for activity-based behaviors; indeed much attention has been paid to promoting healthy habits through social interaction in online communities. In this work we explore how social interaction in activity-based online communities may be structured along demographic features using a large-scale dataset capturing social relationships in a social fitness community over the period of multiple years. We present an analysis of observed gender-based homophily, or more generally selective mixing. We further model the distribution of network size (i.e. degree distribution) for males and females in this context, comparing the stochastic processes that could lead to observed empirical differences, and showing that males and females are observed to have distinct personal network structure.

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