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Grant Details

Grant Number: 1R21CA218231-01 Interpret this number
Primary Investigator: Kavuluru, Venkata Naga Ramakanth
Organization: University Of Kentucky
Project Title: Toward Fine-Grained E-Cigarette Surveillance on Social Media: Evolving Themes, Popularity Predictors, and Demographic Variations
Fiscal Year: 2017


Abstract

ABSTRACT Electronic cigarettes (or e-cigarettes) are currently a popular emerging tobacco product. Because e-cigarettes do not generate toxic tobacco combustion products produced when smoking regular cigarettes, they are perceived and sometimes promoted as a less harmful alternative to smoking and also as a means to quit smoking. Although they may be less harmful, the efficacy of using them for smoking cessation has not been demonstrated conclu- sively with studies indicating evidence both favoring and opposing such an application for them. Furthermore, owing to their recent introduction, there are also safety concerns given reported adverse events. The US Federal Drug Administration (FDA) has introduced regulations that went into effect on 8/8/2016 requiring FDA review for e-cigarette products, banning sales to minors and free samples, and requiring warning labels on certain prod- ucts. In this context, surveillance of evolving themes and factors contributing to message popularity for e-cigarette chatter on social media platforms is an important activity. Twitter has become the favorite network for teenagers and young adults owing to the short message size and associated ease of use on smart phones. For an emerg- ing product like e-cigarettes, the asymmetric follower-friend connections and hashtag functionality in Twitter offer a convenient way to propagate information and facilitate discussion. Among online forums, Reddit allows for longer messages from users inviting specific feedback from other users. Within Reddit, the e-cigarette subreddit facilitates focused discussions on e-cigarette use and products. In this project, we propose to computationally analyze the contents and user profiles available in the dataset of all e-cigarette tweets generated during 7/2016– 6/2017 and all e-cigarette subreddit posts/comments generated since 9/2016. We will continue such analyses with data collected through free but rate limited API throughout the duration of the project. Our first aim is to sur- face specific themes of interest directly from e-cigarette messages using phrase based online and binned topic models. We expect these themes to complement familiar broad themes that researchers currently consider when analyzing online messages. Next, we will identify factors (involving message content and profile characteristics) that contribute to different notions of popularity (#retweets, #replies, #up-votes) of e-cigarette tweets/messages. We expect these results will help health agencies, the FDA, and researchers gain insights into observed viral nature of certain messages and designing effective strategies to maximize diffusion of their messages. Finally, we will conduct these analyses along the dimensions of gender, race, and age to grasp variations in themes and popularity factors specific to different vulnerable demographic segments.



Publications

Opinions on Homeopathy for COVID-19 on Twitter.
Authors: Bopaiah J. , Garimella K. , Kavuluru R. .
Source: Proceedings of the ... ACM Web Science Conference. ACM Web Science Conference, 2022 Jun; 2022, p. 359-363.
EPub date: 2022-06-26.
PMID: 36112977
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Tracking sentiments toward fat acceptance over a decade on Twitter.
Authors: Bograd S. , Chen B. , Kavuluru R. .
Source: Health informatics journal, 2022 Jan-Mar; 28(1), p. 14604582211065702.
PMID: 34986689
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Twitter discourse on nicotine as potential prophylactic or therapeutic for COVID-19.
Authors: Kavuluru R. , Noh J. , Rose S.W. .
Source: The International journal on drug policy, 2022 Jan; 99, p. 103470.
EPub date: 2021-09-20.
PMID: 34607223
Related Citations

Therapeutic Claims in Cannabidiol (CBD) Marketing Messages on Twitter.
Authors: Soleymanpour M. , Saderholm S. , Kavuluru R. .
Source: Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 2021 Dec; 2021, p. 3083-3088.
EPub date: 2022-01-14.
PMID: 35096472
Related Citations

Twitter, Telepractice, and the COVID-19 Pandemic: A Social Media Content Analysis.
Authors: Weidner K. , Lowman J. , Fleischer A. , Kosik K. , Goodbread P. , Chen B. , Kavuluru R. .
Source: American journal of speech-language pathology, 2021-11-04; 30(6), p. 2561-2571.
EPub date: 2021-09-09.
PMID: 34499843
Related Citations

Twitter Discourse on Nicotine as Potential Prophylactic or Therapeutic for COVID-19.
Authors: Kavuluru R. , Noh J. , Rose S.W. .
Source: medRxiv : the preprint server for health sciences, 2021-09-18; , .
EPub date: 2021-09-18.
PMID: 33442710
Related Citations

Identifying current Juul users among emerging adults through Twitter feeds.
Authors: Tran T. , Ickes M.J. , Hester J.W. , Kavuluru R. .
Source: International journal of medical informatics, 2021 Feb; 146, p. 104350.
EPub date: 2020-12-10.
PMID: 33341556
Related Citations

Prevalence and reasons for Juul use among college students.
Authors: Ickes M. , Hester J.W. , Wiggins A.T. , Rayens M.K. , Hahn E.J. , Kavuluru R. .
Source: Journal of American college health : J of ACH, 2020 Jul; 68(5), p. 455-459.
EPub date: 2019-03-26.
PMID: 30913003
Related Citations

Social media surveillance for perceived therapeutic effects of cannabidiol (CBD) products.
Authors: Tran T. , Kavuluru R. .
Source: The International journal on drug policy, 2020 Mar; 77, p. 102688.
EPub date: 2020-02-21.
PMID: 32092666
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On the popularity of the USB flash drive-shaped electronic cigarette Juul.
Authors: Kavuluru R. , Han S. , Hahn E.J. .
Source: Tobacco control, 2019 Jan; 28(1), p. 110-112.
EPub date: 2018-04-13.
PMID: 29654121
Related Citations

Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task.
Authors: Sarker A. , Belousov M. , Friedrichs J. , Hakala K. , Kiritchenko S. , Mehryary F. , Han S. , Tran T. , Rios A. , Kavuluru R. , et al. .
Source: Journal of the American Medical Informatics Association : JAMIA, 2018-10-01; 25(10), p. 1274-1283.
PMID: 30272184
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