Solidarity and Asymmetric Returns in Digital Philanthropy: Division of Labor and Capital Conversion in Weibo’s Stray Dog Rescue Network
DOI:
https://doi.org/10.61360/BoniGHSS262020250306Keywords:
digital philanthropy, stray dog rescue, social network analysis, ERGM, social solidarityAbstract
Stray dog rescue on social media involves both low-cost information circulation and costly offline intervention, yet little is known about how these forms of labor are organized in online networks. Drawing on Durkheim’s theory of social solidarity and Bourdieu’s theory of field and capital, this study analyzes 201 Weibo accounts related to stray dog rescue. A directed following network was examined through social network analysis, exponential random graph modeling, and hierarchical multiple regression. The network contained 6,499 unique directed ties and was fully connected as a weak component, but it also displayed selective ties, local clustering, and unequal central positions. ERGM results show strong homophily by role, capital type, organizational type, and geographic region, while accounts with cross-regional scope, longer tenure, more followers, and more complex rescue functions were more likely to be embedded in the network. Regression results further indicate that engagement rewards were driven mainly by follower base and traffic-cross-over capital rather than by costly offline rescue roles. The findings reveal the coexistence of mechanical and organic solidarity and an asymmetric conversion between rescue labor and platform attention.
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