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Individuals experiencing unexpected distressing events, shocks, often rely ontheir social network for support. While prior work has shown how socialnetworks respond to shocks, these studies usually treat all ties equally,despite differences in the support provided by different social relationships.Here, we conduct a computational analysis on Twitter that examines howresponses to online shocks differ by the relationship type of a user dyad. Weintroduce a new dataset of over 13K instances of individuals' self-reportingshock events on Twitter and construct networks of relationship-labeled dyadicinteractions around these events. By examining behaviors across 110K replies toshocked users in a pseudo-causal analysis, we demonstrate relationship-specificpatterns in response levels and topic shifts. We also show that whilewell-established social dimensions of closeness such as tie strength andstructural embeddedness contribute to shock responsiveness, the degree ofimpact is highly dependent on relationship and shock types. Our findingsindicate that social relationships contain highly distinctive characteristicsin network interactions and that relationship-specific behaviors in onlineshock responses are unique from those of offline settings.

proceedings of the ... international aaai conference on weblogs and social media/proceedings of the international aaai conference on weblogs and social media

Analyzing the Engagement of Social Relationships During Life Event Shocks in Social Media