Disentangling the Network Structure of Online Social Support: A Multilayer Network Analysis of a Twitter Long COVID Community

= 19,196) collected from August 1-31, 2021, we identified two types of social support shared in this community-informational and emotional-through human annotation combined with supervised machine learning. Conducting descriptive and stochastic social network analysis, we examined how exchanges of each type of support were structured. We focused on the density, reciprocity, and centralization of support ties-three structural features shown to be related to specific types of support. Our results showed that informational support was more prevalent than emotional support. Additionally, these informational and emotional support networks tended to be both reciprocal and concentrated around a small number of central users who received considerable support (i.e., were centralized). Our findings suggest that online health communities hosted on platforms such as Twitter may be better suited for informational support. We also observed that central actors play an important role in facilitating these exchanges. These findings provide practical insights for effective social network interventions.