Abstract
This paper examines the generative processes underlying the conversational network structure of a tweet chat community (#dsma, ‘Diabetes Social Media Advocacy’). Taking a relational perspective to the study of mediated communication, this paper uses social network analysis and treats conversational ties as the unit of analysis. It explores the formation of such ties in a multitheoretical, multilevel framework via exponential random graph modeling (ERGM). Twitter network data on #dsma from a two-year period (2015–2017) were analyzed. Results showed that similar to offline relationship formation observed in previous research, this online conversational community also emerged from a combination of social processes (including attribute-based social selection and endogenous network self-organization) that occurred at individual, dyadic, and triadic levels. This study contributes empirical insights into relational dynamics underlying online networks and encourages future research on mediated communication as an emergent, interdependent process involving multifaceted, multilevel mechanisms.
| Original language | English |
|---|---|
| Pages (from-to) | 1463-1480 |
| Journal | Information Communication and Society |
| Volume | 23 |
| Issue number | 10 |
| Online published | 20 Feb 2019 |
| DOIs | |
| Publication status | Published - 2020 |
| Externally published | Yes |
Research Keywords
- exponential random graph modeling (ERGM)
- mediated communication
- multitheoretical multilevel framework
- online relationships
- Social network analysis