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Updated: Sep 20, 2025

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
Exploring possible network properties facilitating recovery for residents of sober living homes
Leonard A Jason1, Ted Bobak1, Mohammed Islam1
1DePaul University, Chicago, USA.
Background:
Recovery homes provide supportive settings for thousands of individuals with substance use disorders each year. However, not all residents of recovery homes improve in these settings, and the reasons for both improvement and lack of improvement are still unclear. It is possible that those low in recovery might benefit when they are in settings with high recovery residents.
Methods:
We examined social network ties among 19 recovery home settings that had pairings of low and high recovery residents.
Results:
We found that low recovery factor individuals generally increased their recovery factor scores over time. In the cases where recovery factor scores did not increase, the low recovery factor individuals had few social network ties with the high recovery residents.
Conclusions:
Both selection and influence can likely be factors that affect recovery behavior in these social settings, as residents may select friends who already exhibit similar behaviors as their own or be influenced by friends to adjust their behavior, so it is more like that of the group. A dynamic systems-based perspective can help investigators better understand how recovery-related behaviors and social relationships co-evolve, and how individual characteristics and house-level social structures can link to changes in individuals' recovery.
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