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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jun 29, 2020
Date Accepted: Sep 16, 2020
Date Submitted to PubMed: Oct 1, 2020

The final, peer-reviewed published version of this preprint can be found here:

Intersection of the Web-Based Vaping Narrative With COVID-19: Topic Modeling Study

Janmohamed K, Soale AN, Forastiere L, Tang W, Sha Y, Massey D, Demant J, Airoldi E, Kumar N

Intersection of the Web-Based Vaping Narrative With COVID-19: Topic Modeling Study

J Med Internet Res 2020;22(10):e21743

DOI: 10.2196/21743

PMID: 33001829

PMCID: 7641646

The intersection of the online vaping narrative with COVID-19: Topic modelling study

  • Kamila Janmohamed; 
  • Abdul-Nasah Soale; 
  • Laura Forastiere; 
  • Weiming Tang; 
  • Yongjie Sha; 
  • Daisy Massey; 
  • Jakob Demant; 
  • Edoardo Airoldi; 
  • Navin Kumar

ABSTRACT

Background:

The spread of the coronavirus disease (Covid-19) is becoming unstoppable and has become a global pandemic as of March 11 2020. The relationship between vaping and contracting Covid-19 is unclear, with conflicting information online. There is some scientific evidence that vaping, cannabidiol (CBD - an active ingredient in cannabis from the hemp plant) or otherwise, may be associated with more severe manifestations of Covid-19. However, there is also inaccurate information that vaping can aid Covid-19 treatment, and expert opinion that CBD, possibly administered through vaping, can mitigate Covid-19 symptoms. Thus, we need to study the spread of inaccurate information to better understand how to promote scientific knowledge and curb inaccurate information, critical to vapers' health. Inaccurate information about vaping and Covid-19 may affect Covid-19 treatment outcomes.

Objective:

Using the novel computational technique of structural topic modelling, we mapped temporal trends in the online vaping narrative (a large dataset comprising online vaping chatter from several sources) to indicate how the narrative changed before versus during Covid-19.

Methods:

We obtained data using a textual query that scanned a data pool of approximately 200000 (5230094 documents and 468961409 words) different domains such as public online forums, blogs and social media from August 1 2019 - April 21 2020. We then used structural topic modelling to understand changes in word prevalence and semantic structures within topics around vaping before and after December 31 2019, when Covid-19 was reported to the World Health Organization (WHO).

Results:

Broadly, the online vaping narrative could be broadly organized into the following groups or archetypes: 1) Harms from vaping; 2) Vaping regulation; 3) Vaping as harm reduction/treatment; 4) Vaping lifestyle. The discourse around CBD, likely administered through vaping, became more prevalent as the pandemic progressed. The emergence of the CBD product preference topic post-Covid-19 report to the World Health Organization may be related to vapers using CBD as a Covid-19 treatment.

Conclusions:

Our main finding is the emergence of a vape-administered CBD treatment narrative around Covid-19, when comparing the pre-Covid-19 versus during Covid-19 online vaping narrative. The strength of this study is our use of innovative computational methods to explore the content of the narrative and how it is affected by Covid-19. Such outcome measurement is key to understanding how vapers respond to inaccurate information about Covid-19, allowing for optimized treatment of vapers who contract Covid-19, and possibly minimizing instances of inaccurate information. Findings have implications for the management of Covid-19 among vapers and monitoring of online content pertinent to tobacco, to develop targeted interventions to manage Covid-19 among vapers.


 Citation

Please cite as:

Janmohamed K, Soale AN, Forastiere L, Tang W, Sha Y, Massey D, Demant J, Airoldi E, Kumar N

Intersection of the Web-Based Vaping Narrative With COVID-19: Topic Modeling Study

J Med Internet Res 2020;22(10):e21743

DOI: 10.2196/21743

PMID: 33001829

PMCID: 7641646

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.