| Sumario: | Background: Social media provides new opportunities for teachers to learn, communicate and develop professional relationships. It has been proved to be a valid and helpful resource for teachers' professional learning purposes. Objectives: While previous studies pursued questions like how participants feel, how to support interaction and why participants remain committed, we asked a more fundamental question: what is the structure of a massive informal online professional learning network and what dynamics can we expect regarding participants' commitment? Methods: This work presents an empirical study of massive informal online professional networks to investigate the dynamics of learning communities and participants' commitment over time. We employed social network analysis and data mining techniques on a longitudinal data set of more than 400,000 tweets published with the hashtag "#edchat." Results and Conclusions: We found that around 30% of participants remained committed to the informal learning community over time. Meanwhile, as more and more people committed to the online learning community, participants tended to form smaller communities where the internal connection was stronger. Takeaways: In informal online learning environments, participants can form stable connections. The 30% threshold can be used to measure massive informal online learning networks in terms of commitment or persistence. Lay Description: What is already known about this topic: Social media has been proved to be a valid and helpful resource for teachers' professional learning purposes.Most previous work heavily relied on qualitative methods and self‐report data, focusing on how social‐media‐based professional learning promotes teachers' connections and how participants perceive these tools.There is a lack in quantitative analysis to investigate the large informal professional learning networks using authentic data. What this paper adds: This study examined massive informal professional learning networks on Twitter, using a data set of more than 400,000 tweets.Through the lens of community commitment, we provided a comprehensive and in‐depth overview of the structure and development of massive informal online professional networks.This study examined the commitment dynamics from multiple perspectives: network level, community level, and individual level.This study utilized social network analysis and data mining techniques to identify meaningful structures, participants' commitment dynamics, and behavioural patterns at the network, community and individual levels. Implications for practice and/or policy: Methodologically, the usage of longitudinal data enabled a temporal perspective to our analysis.Our finding that around 30% of the participants remain committed to the learning network without intervention could be used as a benchmark in assessing informal online learning networks.We identified a natural cluster pattern that participants tend to form communities with peers who behave similarly, providing reference for developers and moderators of informal online learning.
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