Grant Details
Grant Number: |
7R01CA225773-05 Interpret this number |
Primary Investigator: |
Primack, Brian |
Organization: |
Oregon State University |
Project Title: |
Leveraging Twitter to Monitor Nicotine and Tobacco Cancer Communication |
Fiscal Year: |
2022 |
Abstract
Patterns in Twitter data have revolutionized understanding of public health events such as influenza outbreaks.
While researchers have begun to examine messaging related to substance use on Twitter, this project will
strengthen the use of Twitter as an infoveillance tool to more rigorously examine nicotine, tobacco, and cancer-
related communication. Twitter is particularly suited to this work because its users are commonly adolescents,
young adults, and racial and ethnic minorities, all of whom are at increased risk for nicotine and tobacco
product (NTP) use and related health consequences. Additionally, due to the openness of the platform,
searches are replicable and transparent, enabling large-scale systematic research. Therefore, our
multidisciplinary team of experts in diverse relevant fields—including public health, behavioral science,
computational linguistics, computer science, biomedical informatics, and information privacy and security—will
build upon our previous research to develop and validate structured algorithms providing automated
surveillance of Twitter’s multifaceted and continuously evolving information related to NTPs. First, we will
qualitatively assess a stratified random sample of relevant NTP-related tweets for specific coded variables,
such as the message’s primary sentiment and other key information of potential value (e.g., whether a
message involves buying/selling, policy/law, and cancer-related communication). Tweets will be obtained
directly from Twitter using software we developed that leverages a comprehensive list of Twitter-optimized
search strings related to NTPs. Second, we will statistically determine what message characteristics (e.g., the
presence of certain words, punctuation, and/or structures) are most strongly associated with each of the coded
variables for each search string. Using this information, we will create specialized Machine Learning (ML)
algorithms based on state-of-the-art methods from Natural Language Processing (NLP) to automatically
assess and categorize future Twitter data. Third, we will use this information to provide automatic assessment
of current and future streaming data. Time series analyses using seasonal Auto-Regressive Integrated Moving
Averages (ARIMA) will determine if there are significant changes over time in volume of messaging related to
each specific coded variables of interest. Trends will be examined at the daily, weekly, and monthly level,
because each of these levels is potentially valuable for intervention. To maximize the translational value of this
project, we will partner with public health department stakeholders who are experts in streamlining
dissemination of actionable trends data. In summary, this project will substantially advance our understanding
of representations of NTPs on social media—as well as our ability to conduct automated surveillance and
analysis of this content. This project will result in important and concrete deliverables, including open-source
algorithms for future researchers and processes to quickly disseminate actionable data for tailoring community-
level interventions.
Publications
Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis.
Authors: Dobbs P.D.
, Boykin A.A.
, Ezike N.
, Myers A.J.
, Colditz J.B.
, Primack B.A.
.
Source: Jmir Formative Research, 2023-08-31 00:00:00.0; 7, p. e50346.
EPub date: 2023-08-31 00:00:00.0.
PMID: 37651169
Related Citations
Viewer Reactions to EVALI Storylines on Popular Medical Dramas: A Thematic Analysis of Twitter Messages.
Authors: Hoffman B.L.
, Wolynn R.
, Barrett E.
, Manganello J.A.
, Felter E.M.
, Sidani J.E.
, Miller E.
, Burke J.G.
, Primack B.A.
, Chu K.H.
.
Source: Journal Of Health Communication, 2023-05-04 00:00:00.0; 28(5), p. 282-291.
EPub date: 2023-04-14 00:00:00.0.
PMID: 37057592
Related Citations
Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study.
Authors: Baker W.
, Colditz J.B.
, Dobbs P.D.
, Mai H.
, Visweswaran S.
, Zhan J.
, Primack B.A.
.
Source: Jmir Medical Informatics, 2022-07-21 00:00:00.0; 10(7), p. e33678.
EPub date: 2022-07-21 00:00:00.0.
PMID: 35862172
Related Citations
Analyzing Twitter Chatter About Tobacco Use Within Intoxication-related Contexts of Alcohol Use: "Can Someone Tell Me Why Nicotine is So Fire When You're Drunk?"
Authors: Russell A.M.
, Colditz J.B.
, Barry A.E.
, Davis R.E.
, Shields S.
, Ortega J.M.
, Primack B.
.
Source: Nicotine & Tobacco Research : Official Journal Of The Society For Research On Nicotine And Tobacco, 2022-07-13 00:00:00.0; 24(8), p. 1193-1200.
PMID: 34562100
Related Citations
Discussions and Misinformation About Electronic Nicotine Delivery Systems and COVID-19: Qualitative Analysis of Twitter Content.
Authors: Sidani J.E.
, Hoffman B.
, Colditz J.B.
, Wolynn R.
, Hsiao L.
, Chu K.H.
, Rose J.J.
, Shensa A.
, Davis E.
, Primack B.
.
Source: Jmir Formative Research, 2022-04-13 00:00:00.0; 6(4), p. e26335.
EPub date: 2022-04-13 00:00:00.0.
PMID: 35311684
Related Citations
Discussions and Misinformation About Electronic Nicotine Delivery Systems and COVID-19: Qualitative Analysis of Twitter Content.
Authors: Sidani J.E.
, Hoffman B.
, Colditz J.B.
, Wolynn R.
, Hsiao L.
, Chu K.H.
, Rose J.J.
, Shensa A.
, Davis E.
, Primack B.
.
Source: Jmir Formative Research, 2022-04-13 00:00:00.0; 6(4), p. e26335.
EPub date: 2022-04-13 00:00:00.0.
PMID: 35311684
Related Citations
Puff Bars, Tobacco Policy Evasion, and Nicotine Dependence: Content Analysis of Tweets.
Authors: Chu K.H.
, Hershey T.B.
, Hoffman B.L.
, Wolynn R.
, Colditz J.B.
, Sidani J.E.
, Primack B.A.
.
Source: Journal Of Medical Internet Research, 2022-03-25 00:00:00.0; 24(3), p. e27894.
EPub date: 2022-03-25 00:00:00.0.
PMID: 35333188
Related Citations
Policy and Behavior: Comparisons between Twitter Discussions about the US Tobacco 21 Law and Other Age-Related Behaviors.
Authors: Dobbs P.D.
, Colditz J.B.
, Shields S.
, Meadows A.
, Primack B.A.
.
Source: International Journal Of Environmental Research And Public Health, 2022-02-24 00:00:00.0; 19(5), .
EPub date: 2022-02-24 00:00:00.0.
PMID: 35270306
Related Citations
Miscommunication about the US federal Tobacco 21 law: a content analysis of Twitter discussions.
Authors: Dobbs P.D.
, Schisler E.
, Colditz J.B.
, Primack B.A.
.
Source: Tobacco Control, 2022-02-16 00:00:00.0; , .
EPub date: 2022-02-16 00:00:00.0.
PMID: 35173067
Related Citations
E-Cigarette-Related Nicotine Misinformation on Social Media.
Authors: Sidani J.E.
, Hoffman B.L.
, Colditz J.B.
, Melcher E.
, Taneja S.B.
, Shensa A.
, Primack B.
, Davis E.
, Chu K.H.
.
Source: Substance Use & Misuse, 2022; 57(4), p. 588-594.
EPub date: 2022-01-22 00:00:00.0.
PMID: 35068338
Related Citations
E-Cigarette-Related Nicotine Misinformation on Social Media.
Authors: Sidani J.E.
, Hoffman B.L.
, Colditz J.B.
, Melcher E.
, Taneja S.B.
, Shensa A.
, Primack B.
, Davis E.
, Chu K.H.
.
Source: Substance Use & Misuse, 2022; 57(4), p. 588-594.
EPub date: 2022-01-22 00:00:00.0.
PMID: 35068338
Related Citations
Collaborative Public Health Strategies to Combat e-Cigarette Regulation Loopholes.
Authors: Chu K.H.
, Hershey T.B.
, Sidani J.E.
.
Source: Jama Pediatrics, 2021-11-01 00:00:00.0; 175(11), p. 1102-1104.
PMID: 34398212
Related Citations
Re-evaluating standards of human subjects protection for sensitive health data in social media networks.
Authors: Chu K.H.
, Colditz J.
, Sidani J.
, Zimmer M.
, Primack B.
.
Source: Social Networks, 2021 Oct; 67, p. 41-46.
EPub date: 2019-11-20 00:00:00.0.
PMID: 34539049
Related Citations
#Alcohol: Portrayals of Alcohol in Top Videos on TikTok.
Authors: Russell A.M.
, Davis R.E.
, Ortega J.M.
, Colditz J.B.
, Primack B.
, Barry A.E.
.
Source: Journal Of Studies On Alcohol And Drugs, 2021 09; 82(5), p. 615-622.
PMID: 34546908
Related Citations
#DoctorsSpeakUp: Lessons learned from a pro-vaccine Twitter event.
Authors: Hoffman B.L.
, Colditz J.B.
, Shensa A.
, Wolynn R.
, Taneja S.B.
, Felter E.M.
, Wolynn T.
, Sidani J.E.
.
Source: Vaccine, 2021-05-06 00:00:00.0; 39(19), p. 2684-2691.
EPub date: 2021-04-13 00:00:00.0.
PMID: 33863574
Related Citations
Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study.
Authors: Visweswaran S.
, Colditz J.B.
, O'Halloran P.
, Han N.R.
, Taneja S.B.
, Welling J.
, Chu K.H.
, Sidani J.E.
, Primack B.A.
.
Source: Journal Of Medical Internet Research, 2020-08-12 00:00:00.0; 22(8), p. e17478.
EPub date: 2020-08-12 00:00:00.0.
PMID: 32784184
Related Citations
Integrating Social Dynamics Into Modeling Cigarette and E-Cigarette Use.
Authors: Chu K.H.
, Shensa A.
, Colditz J.B.
, Sidani J.E.
, Hoffman B.L.
, Sinclair D.
, Krauland M.G.
, Primack B.A.
.
Source: Health Education & Behavior : The Official Publication Of The Society For Public Health Education, 2020 Apr; 47(2), p. 191-201.
EPub date: 2020-02-24 00:00:00.0.
PMID: 32090652
Related Citations
JUUL on Twitter: Analyzing Tweets About Use of a New Nicotine Delivery System.
Authors: Sidani J.E.
, Colditz J.B.
, Barrett E.L.
, Chu K.H.
, James A.E.
, Primack B.A.
.
Source: The Journal Of School Health, 2019-12-11 00:00:00.0; , .
EPub date: 2019-12-11 00:00:00.0.
PMID: 31828791
Related Citations
I wake up and hit the JUUL: Analyzing Twitter for JUUL nicotine effects and dependence.
Authors: Sidani J.E.
, Colditz J.B.
, Barrett E.L.
, Shensa A.
, Chu K.H.
, James A.E.
, Primack B.A.
.
Source: Drug And Alcohol Dependence, 2019-11-01 00:00:00.0; 204, p. 107500.
EPub date: 2019-08-30 00:00:00.0.
PMID: 31499242
Related Citations
Identifying Key Target Audiences for Public Health Campaigns: Leveraging Machine Learning in the Case of Hookah Tobacco Smoking.
Authors: Chu K.H.
, Colditz J.
, Malik M.
, Yates T.
, Primack B.
.
Source: Journal Of Medical Internet Research, 2019-07-08 00:00:00.0; 21(7), p. e12443.
EPub date: 2019-07-08 00:00:00.0.
PMID: 31287063
Related Citations
JUUL: Spreading Online and Offline.
Authors: Chu K.H.
, Colditz J.B.
, Primack B.A.
, Shensa A.
, Allem J.P.
, Miller E.
, Unger J.B.
, Cruz T.B.
.
Source: The Journal Of Adolescent Health : Official Publication Of The Society For Adolescent Medicine, 2018 Nov; 63(5), p. 582-586.
PMID: 30348280
Related Citations
Toward Real-Time Infoveillance of Twitter Health Messages.
Authors: Colditz J.B.
, Chu K.H.
, Emery S.L.
, Larkin C.R.
, James A.E.
, Welling J.
, Primack B.A.
.
Source: American Journal Of Public Health, 2018 Aug; 108(8), p. 1009-1014.
EPub date: 2018-06-21 00:00:00.0.
PMID: 29927648
Related Citations