Analyzing the Engagement of Social Relationships During Life Event Shocks in Social Media
Minje Choi, David Jurgens, Daniel M. Romero

TL;DR
This study analyzes how different types of social relationships on Twitter influence responses to life shocks, revealing relationship-specific patterns and the importance of relationship characteristics in online support behaviors.
Contribution
Introduces a new dataset and computational framework to analyze relationship-specific responses to shocks on Twitter, highlighting the variability based on relationship and shock types.
Findings
Relationship-specific response patterns identified
Tie strength and embeddedness influence shock responsiveness
Online shock responses differ from offline behaviors
Abstract
Individuals experiencing unexpected distressing events, shocks, often rely on their social network for support. While prior work has shown how social networks 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 how responses to online shocks differ by the relationship type of a user dyad. We introduce a new dataset of over 13K instances of individuals' self-reporting shock events on Twitter and construct networks of relationship-labeled dyadic interactions around these events. By examining behaviors across 110K replies to shocked users in a pseudo-causal analysis, we demonstrate relationship-specific patterns in response levels and topic shifts. We also show that while well-established social dimensions of closeness such as tie…
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Taxonomy
TopicsMental Health via Writing · Mental Health Research Topics · Digital Mental Health Interventions
