ArticleJournal of medical Internet research2017
Patterns of Twitter Behavior Among Networks of Cannabis Dispensaries in California.
Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed.
- Cannabis Retailer Communication About Cannabis Products, Health Benefits, and Risks: A Mystery Shopper Study of Licensed Retailers in Five U.S. Cities.Journal of studies on alcohol and drugs · 2024Article
- The Volume and Tone of Twitter Posts About Cannabis Use During Pregnancy: Protocol for a Scoping Review.JMIR research protocols · 2022Article
- Infodemiology and Infoveillance: Scoping Review.Journal of medical Internet research · 2020Article
- Interpol review of controlled substances 2016-2019.Forensic science international. Synergy · 2020Review
- Cannabis regulatory science: risk-benefit considerations for mental disorders.International review of psychiatry (Abingdon, England) · 2018Review
- Studying Cannabis Use Behaviors With Facebook and Web Surveys: Methods and Insights.JMIR public health and surveillance · 2018Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTwitter represents a social media platform through which medical cannabis dispensaries can rapidly promote and advertise a multitude of retail products. Yet, to date, no studies have systematically evaluated Twitter behavior among dispensaries and how these behaviors influence the formation of social networks.
objectivesThis study sought to characterize common cyberbehaviors and shared follower networks among dispensaries operating in two large cannabis markets in California.
methodsFrom a targeted sample of 119 dispensaries in the San Francisco Bay Area and Greater Los Angeles, we collected metadata from the dispensary accounts using the Twitter API. For each city, we characterized the network structure of dispensaries based upon shared followers, then empirically derived communities with the Louvain modularity algorithm. Principal components factor analysis was employed to reduce 12 Twitter measures into a more parsimonious set of cyberbehavioral dimensions. Finally, quadratic discriminant analysis was implemented to verify the ability of the extracted dimensions to classify dispensaries into their derived communities.
resultsThe modularity algorithm yielded three communities in each city with distinct network structures. The principal components factor analysis reduced the 12 cyberbehaviors into five dimensions that encompassed account age, posting frequency, referencing, hyperlinks, and user engagement among the dispensary accounts. In the quadratic discriminant analysis, the dimensions correctly classified 75% (46/61) of the communities in the San Francisco Bay Area and 71% (41/58) in Greater Los Angeles.
conclusionsThe most centralized and strongly connected dispensaries in both cities had newer accounts, higher daily activity, more frequent user engagement, and increased usage of embedded media, keywords, and hyperlinks. Measures derived from both network structure and cyberbehavioral dimensions can serve as key contextual indicators for the online surveillance of cannabis dispensaries and consumer markets over time.
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