The Pursuit of Peer Support for Opioid Use Recovery on Reddit

Balsamo, Duilio; Bajardi, Paolo; Morales, Gianmarco De Francisci; Monti, Corrado; Schifanella, Rossano

doi:10.1609/icwsm.v17i1.22122

Cited by 4 publications

(3 citation statements)

References 53 publications

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“…We are interested in understanding whether this declared change in opinion is related to a change in information consumption behavior in the future. Previous work (Massachs et al 2020;Balsamo, Bajardi, and Panisson 2019;Balsamo et al 2023) has showed that participation in subreddits is a valuable proxy for a wide range of characteristics of the user. For this reason, we take the subreddits they participate in-their communities on Reddit-as a meaningful measure of the behavior of the user.…”

Section: Datamentioning

confidence: 99%

“…Furthermore, we limit the time frame in which we observe behavioral change by considering only comments written at most one year before or after the date of the user's post on CMV. We do so in order to consider in our analyses only events of online behavior change that are relatively close in time to the reported opinion change, and that can thus be considered related to it more reliably (Balsamo et al 2023). We indicate with b u,s and a u,s the number of comments authored by user u on subreddit s before and after (respectively) their post on r/ChangeMyView, limited to the time frame described above.…”

Section: Datamentioning

confidence: 99%

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On the Relation between Opinion Change and Information Consumption on Reddit

Flavio

Bonchi²,

Morales³

et al. 2023

ICWSM

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While much attention has been devoted to the causes of opinion change, little is known about its consequences. Our study moves a first step in this direction by looking at Reddit, and in particular to the subreddit r/ChangeMyView, a community dedicated to debating one’s own opinions on a wide array of topics. We analyze changes in online information consumption behavior that arise after a self-reported opinion change, by looking at the participation to a set of sociopolitical communities. We find that people who self-report an opinion change are significantly more likely to change their future participation in a specific subset of those communities. Specifically, there is a significant association (Pearson r = 0.46) between using propaganda-like language in a community and the increase in chances of leaving it. Comparable results (Pearson r = 0.39) hold for the opposite direction, i.e., joining these same communities. In addition, the textual content of the post associated with opinion change is indicative of which communities will be joined or left: a predictive model based only on the text of this post can pinpoint these communities with an average precision@5 of 0.20. Our results establish a link between opinion change and information consumption, and highlight how online propagandistic communities act as a first gateway to internalize a shift in one’s sociopolitical opinion.

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Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

On the Relation between Opinion Change and Information Consumption on Reddit

Flavio

Bonchi²,

Morales³

et al. 2023

ICWSM

View full text Add to dashboard Cite

show abstract

“…Nevertheless, the data from social media are invaluable for research. The information gathered from social media platforms is timely and relevant for studying substance use characteristics longitudinally [ 17 - 19 ]. As a result, the data obtained from social media offer a unique opportunity to observe substance use behaviors within a broad population, enabling a deeper comprehension of the underlying patterns and factors influencing substance use behaviors.…”

Section: Introductionmentioning

confidence: 99%

Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach

Yuan,

Kasson,

Taylor

et al. 2024

JMIR Form Res

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Background Substance misuse presents significant global public health challenges. Understanding transitions between substance types and the timing of shifts to polysubstance use is vital to developing effective prevention and recovery strategies. The gateway hypothesis suggests that high-risk substance use is preceded by lower-risk substance use. However, the source of this correlation is hotly contested. While some claim that low-risk substance use causes subsequent, riskier substance use, most people using low-risk substances also do not escalate to higher-risk substances. Social media data hold the potential to shed light on the factors contributing to substance use transitions. Objective By leveraging social media data, our study aimed to gain a better understanding of substance use pathways. By identifying and analyzing the transitions of individuals between different risk levels of substance use, our goal was to find specific linguistic cues in individuals’ social media posts that could indicate escalating or de-escalating patterns in substance use. Methods We conducted a large-scale analysis using data from Reddit, collected between 2015 and 2019, consisting of over 2.29 million posts and approximately 29.37 million comments by around 1.4 million users from subreddits. These data, derived from substance use subreddits, facilitated the creation of a risk transition data set reflecting the substance use behaviors of over 1.4 million users. We deployed deep learning and machine learning techniques to predict the escalation or de-escalation transitions in risk levels, based on initial transition phases documented in posts and comments. We conducted a linguistic analysis to analyze the language patterns associated with transitions in substance use, emphasizing the role of n-gram features in predicting future risk trajectories. Results Our results showed promise in predicting the escalation or de-escalation transition in risk levels, based on the historical data of Reddit users created on initial transition phases among drug-related subreddits, with an accuracy of 78.48% and an F1-score of 79.20%. We highlighted the vital predictive features, such as specific substance names and tools indicative of future risk escalations. Our linguistic analysis showed that terms linked with harm reduction strategies were instrumental in signaling de-escalation, whereas descriptors of frequent substance use were characteristic of escalating transitions. Conclusions This study sheds light on the complexities surrounding the gateway hypothesis of substance use through an examination of web-based behavior on Reddit. While certain findings validate the hypothesis, indicating a progression from lower-risk substances such as marijuana to higher-risk ones, a significant number of individuals did not show this transition. The research underscores the potential of using machine learning with social media analysis to predict substance use transitions. Our results point toward future directions for leveraging social media data in substance use research, underlining the importance of continued exploration before suggesting direct implications for interventions.

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Drivers of social influence in the Twitter migration to Mastodon

Cava,

Aiello,

Tagarelli

2023

Sci Rep

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The migration of Twitter users to Mastodon following Elon Musk’s acquisition presents a unique opportunity to study collective behavior and gain insights into the drivers of coordinated behavior in online media. We analyzed the social network and the public conversations of about 75,000 migrated users and observed that the temporal trace of their migrations is compatible with a phenomenon of social influence, as described by a compartmental epidemic model of information diffusion. Drawing from prior research on behavioral change, we delved into the factors that account for variations of the effectiveness of the influence process across different Twitter communities. Communities in which the influence process unfolded more rapidly exhibit lower density of social connections, higher levels of signaled commitment to migrating, and more emphasis on shared identity and exchange of factual knowledge in the community discussion. These factors account collectively for 57% of the variance in the observed data. Our results highlight the joint importance of network structure, commitment, and psycho-linguistic aspects of social interactions in characterizing grassroots collective action, and contribute to deepen our understanding of the mechanisms that drive processes of behavior change of online groups.

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The Pursuit of Peer Support for Opioid Use Recovery on Reddit

Cited by 4 publications

References 53 publications

On the Relation between Opinion Change and Information Consumption on Reddit

On the Relation between Opinion Change and Information Consumption on Reddit

Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach

Drivers of social influence in the Twitter migration to Mastodon

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