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Cell Biology JoVE (Open Access) Citable · DOI

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

DOI: 10.3791/58851-v
What you'll learn
  • ✓ Extract and prepare online community data for computational analysis
  • ✓ Apply social network analysis to map peer support dynamics
  • ✓ Use linguistic analysis to predict community retention outcomes
  • ✓ Integrate multiple analytical methods to assess recovery capital
Protocol

The article describes a novel approach for analyzing dynamic online social interactions (in an online context) exemplified by a study of an online community of recovery from alcohol and drug addiction.

Difficulty
advanced
Total time
~4–8 weeks (data collection and analysis per cohort)

Steps

1
Extract online community interaction data

Identify and collect posts, messages, and engagement records from the online recovery community platform. Prepare raw data for downstream computational processing.

▶ 00:25
2
Calculate social media activity metrics per user

Quantify the number of social interactions made and received by each community member. Standardize activity metrics for comparative analysis across participants.

▶ 01:42
3
Perform social network analysis mapping

Apply SNA algorithms to visualize peer support connections, node centrality, and community clustering patterns. Identify influential members and structural network properties.

▶ 02:46
4
Conduct linguistic and regression analyses

Use computerized text analysis to extract linguistic features from posts. Perform regression modeling to link linguistic markers and network metrics to recovery outcomes.

▶ 03:55
5
Generate monthly network maps and aggregate activity

Create time-series snapshots of network topology and cumulative social media activity by month. Track longitudinal shifts in community structure and engagement.

▶ 05:44
6
Analyze SNA predictors of community retention

Evaluate which network metrics and linguistic features correlate with participant retention in the online recovery community. Validate predictive models on representative cohorts.

▶ 06:57
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