ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2016
Content-specific network analysis of peer-to-peer communication in an online community for smoking cessation.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Content matters, context matters: unraveling behavior dynamics in an online health community for tobacco cessation.JAMIA open · 2026Article
- Discerning conversational context in online health communities for personalized digital behavior change solutions using Pragmatics to Reveal Intent in Social Media (PRISM) framework.Journal of biomedical informatics · 2023Article
- Pragmatics to Reveal Intent in Social Media Peer Interactions: Mixed Methods Study.Journal of medical Internet research · 2021Article
- Transitions Between Electronic and Combustible Cigarettes: A Mixed Methods Analysis of Peer Interactions in an Online Community for Tobacco Cessation.Studies in health technology and informatics · 2021Article
- Exchanges in a Virtual Environment for Diabetes Self-Management Education and Support: Social Network Analysis.JMIR diabetes · 2021Article
- Diabetes Self-Management in the Age of Social Media: Large-Scale Analysis of Peer Interactions Using Semiautomated Methods.JMIR medical informatics · 2020Article
- Exploring the Social Structure of a Health-Related Online Community for Tobacco Cessation: A Two-Mode Network Approach.Studies in health technology and informatics · 2019Article
- Content-Sensitive Characterization of Peer Interactions of Highly Engaged Users in an Online Community for Smoking Cessation: Mixed-Methods Approach for Modeling User Engagement in Health Promotion Interventions.Journal of participatory medicine · 2018Article
- Characterization of Temporal Semantic Shifts of Peer-to-Peer Communication in a Health-Related Online Community: Implications for Data-driven Health Promotion.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Analysis of user interactions in online communities could improve our understanding of health-related behaviors and inform the design of technological solutions that support behavior change. However, to achieve this we would need methods that provide granular perspective, yet are scalable. In this paper, we present a methodology for high-throughput semantic and network analysis of large social media datasets, combining semi-automated text categorization with social network analytics. We apply this method to derive content-specific network visualizations of 16,492 user interactions in an online community for smoking cessation. Performance of the categorization system was reasonable (average F-measure of 0.74, with system-rater reliability approaching rater-rater reliability). The resulting semantically specific network analysis of user interactions reveals content- and behavior-specific network topologies. Implications for socio-behavioral health and wellness platforms are also discussed.
Indexed as
Identifiers
28269890PMC5333292What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.