Grant Number:	5R01CA192345-03 Interpret this number
Primary Investigator:	Graham, Amanda
Organization:	Truth Initiative Foundation
Project Title:	Social Dynamics of Substance Use in Online Social Networks for Smoking Cessation
Fiscal Year:	2016

DESCRIPTION (provided by applicant): Millions of smokers turn to the Internet each year for cessation assistance and hundreds of thousands seek advice and support in online social networks for smoking cessation. Though it has been nearly 15 years since the first online social network for smoking cessation was launched, little is known about the ways in which online social networks impact tobacco use. This study will examine how online social networks influence smoking cessation. Our multidisciplinary team of behavioral and computational social scientists will conduct an in-depth examination of a 6-year longitudinal dataset from a large online social network for smoking cessation with over 650,000 members. In addition to core components of tobacco dependence treatment, there are multiple modes for communication (e.g., forums, private messaging, wall posts), self-representation (e.g., personal profiles, blogs) and affiliation (e.g., friends). All actions are date/time stamped. The dataset contains transactional data on all users, including active events from "posters" (e.g., writing messages and blogs), passive events from "lurkers" (e.g., reading forum posts and profiles), and de-identified content of public and private communications. Embedded within this network are N=5,000 participants in an ongoing randomized trial and a distinct sample of N=1,033 participants in a 2011 cohort study. Smoking status at 3 months is known on about 60% of these participants. This unique trove of as-yet unexplored longitudinal social network data makes it possible to examine the impact of social dynamics on smoking cessation. Using modern and innovative social computing methods, we will examine social network dynamics, sentiment, and social support in the entire network (NH650,000). We will begin with social network analyses to construct metrics of the dynamic topology of the overall network. Next, we will conduct sophisticated sentiment analyses to construct metrics of social influence dynamics regarding "hot topics" in the online community (e.g., "cold turkey" vs. pharmacotherapy, e- cigarettes as a cessation device). We will use fine-grained text analytics to parse language related to social support (e.g., informational, appraisal) and language that signals smoking status (e.g., quit anniversaries, smoking slips). We will also examine communications related to alcohol use and problem drinking. This broad range of metrics will be used to achieve the following Specific Aims: (1) Examine social network dynamics, sentiment dynamics, and social support as predictors of 3-month smoking abstinence in the N=5,000 sample, and validate results in the N=1,033 sample; (2) Examine social network processes related to tobacco and alcohol use; and (3) Explore the correspondence between smoking status discerned from text analytics and 3-month abstinence outcomes to determine the feasibility of estimating quit rates in online social networks for cessation. This study will significantly advance methods for the study of online social networks for smoking cessation. Our work will hone computational methods that have been broadly applied in other fields but have yet to inform tobacco dependence treatment.




Twelve Million Smokers Look Online for Smoking Cessation Help Annually: Health Information National Trends Survey Data, 2005-2017.
Authors: Graham A.L. , Amato M.S. .
Source: Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2019-01-04; 21(2), p. 249-252.
PMID: 29660037
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Inferring Smoking Status from User Generated Content in an Online Cessation Community.
Authors: Amato M.S. , Papandonatos G.D. , Cha S. , Wang X. , Zhao K. , Cohn A.M. , Pearson J.L. , Graham A.L. .
Source: Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2019-01-04; 21(2), p. 205-211.
PMID: 29365157
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Mining User-Generated Content in an Online Smoking Cessation Community to Identify Smoking Status: A Machine Learning Approach.
Authors: Wang X. , Zhao K. , Cha S. , Amato M.S. , Cohn A.M. , Pearson J.L. , Papandonatos G.D. , Graham A.L. .
Source: Decision support systems, 2019 Jan; 116, p. 26-34.
EPub date: 2018-10-15.
PMID: 31885411
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Discussions of Alcohol Use in an Online Social Network for Smoking Cessation: Analysis of Topics, Sentiment, and Social Network Centrality.
Authors: Cohn A.M. , Amato M.S. , Zhao K. , Wang X. , Cha S. , Pearson J.L. , Papandonatos G.D. , Graham A.L. .
Source: Alcoholism, clinical and experimental research, 2019 Jan; 43(1), p. 108-114.
EPub date: 2018-11-19.
PMID: 30326140
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Exposure to positive peer sentiment about nicotine replacement therapy in an online smoking cessation community is associated with NRT use.
Authors: Pearson J.L. , Amato M.S. , Papandonatos G.D. , Zhao K. , Erar B. , Wang X. , Cha S. , Cohn A.M. , Graham A.L. .
Source: Addictive behaviors, 2018 Dec; 87, p. 39-45.
EPub date: 2018-06-19.
PMID: 29940390
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The failure to increase social support: it just might be time to stop intervening (and start rigorously observing).
Authors: Graham A.L. , Papandonatos G.D. , Zhao K. .
Source: Translational behavioral medicine, 2017 Dec; 7(4), p. 816-820.
PMID: 28070778
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A Descriptive Study of the Prevalence and Typology of Alcohol-Related Posts in an Online Social Network for Smoking Cessation.
Authors: Cohn A.M. , Zhao K. , Cha S. , Wang X. , Amato M.S. , Pearson J.L. , Papandonatos G.D. , Graham A.L. .
Source: Journal of studies on alcohol and drugs, 2017 Sep; 78(5), p. 665-673.
PMID: 28930053
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How US Smokers Refer to E-cigarettes: An Examination of User-Generated Posts From a Web-Based Smoking Cessation Intervention, 2008-2015.
Authors: Pearson J.L. , Amato M.S. , Wang X. , Zhao K. , Cha S. , Cohn A.M. , Papandonatos G.D. , Graham A.L. .
Source: Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2017 Feb; 19(2), p. 253-257.
EPub date: 2016-08-16.
PMID: 27613899
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A prospective examination of online social network dynamics and smoking cessation.
Authors: Graham A.L. , Zhao K. , Papandonatos G.D. , Erar B. , Wang X. , Amato M.S. , Cha S. , Cohn A.M. , Pearson J.L. .
Source: PloS one, 2017; 12(8), p. e0183655.
EPub date: 2017-08-23.
PMID: 28832621
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A Multirelational Social Network Analysis of an Online Health Community for Smoking Cessation.
Authors: Zhao K. , Wang X. , Cha S. , Cohn A.M. , Papandonatos G.D. , Amato M.S. , Pearson J.L. , Graham A.L. .
Source: Journal of medical Internet research, 2016-08-25; 18(8), p. e233.
EPub date: 2016-08-25.
PMID: 27562640
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A Preliminary Exploration of Former Smokers Enrolled in an Internet Smoking Cessation Program.
Authors: Cha S. , Cohn A.M. , Elmasry H. , Graham A.L. .
Source: JMIR research protocols, 2016-06-14; 5(2), p. e119.
EPub date: 2016-06-14.
PMID: 27302500
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