0
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Intent mining framework for understanding online conversations on vaping to inform social media-based intervention design

, , &
Received 26 Aug 2023, Accepted 06 Jul 2024, Published online: 24 Jul 2024
 

ABSTRACT

The recent surge in the usage of e-cigarettes amongst youth has highlighted a long-standing societal crisis. To assist public health agencies in policymaking, past research often employed traditional survey-based methods to understand youth behavior, which suffer from response biases and scalability, are time-consuming, and their findings often lag the fast-changing public behavior. Our study fills this gap by using social media as a complementary data source to understand user intentions for vape usage at a large scale, thus, providing an alternative to traditional survey-based methods. In this paper, we propose a novel user intent mining framework under the guidance of social cognitive theory for health behavioral interventions that helps study user intentions across different social media platforms. We then employ this framework to investigate the feasibility of automated intent mining on social media by formulating a multi-class classification task, employing machine learning algorithms to classify a social media message across relevant intent classes: Accusational, Anecdotal, Informational, Justificational and Promotional. The analyses indicate that Accusational tweets and Anecdotal messages were most prevalent on X/Twitter and Reddit respectively. We further provide novel insights on the conversational context using topic modeling analysis and psychometric analysis consequently, informing intervention designs and assisting health analysts.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 333.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.