This paper is in the following e-collection/theme issue:

Infodemiology and Infoveillance (1369)

Published on in Vol 15, No 8 (2013): August

Using Twitter to Examine Smoking Behavior and Perceptions of Emerging Tobacco Products

Using Twitter to Examine Smoking Behavior and Perceptions of Emerging Tobacco Products

Using Twitter to Examine Smoking Behavior and Perceptions of Emerging Tobacco Products

Authors of this article:

Mark Myslín1 ;   Shu-Hong Zhu2 ;   Wendy Chapman3 ;   Mike Conway3
Article Authors Cited by (235) Tweetations (59) Metrics

Journals

  1. Kazemi D, Borsari B, Levine M, Dooley B. Systematic review of surveillance by social media platforms for illicit drug use. Journal of Public Health 2017;39(4):763 View
  2. Skinner A, Attwood A, Baddeley R, Evans-Reeves K, Bauld L, Munafò M. Digital phenotyping and the development and delivery of health guidelines and behaviour change interventions. Addiction 2017;112(7):1281 View
  3. Zhu Y. Pro-smoking information scanning using social media predicts young adults' smoking behavior. Computers in Human Behavior 2017;77:19 View
  4. Hswen Y, Naslund J, Chandrashekar P, Siegel R, Brownstein J, Hawkins J. Exploring online communication about cigarette smoking among Twitter users who self-identify as having schizophrenia. Psychiatry Research 2017;257:479 View
  5. Steers M, Moreno M, Neighbors C. The Influence of Social Media on Addictive Behaviors in College Students. Current Addiction Reports 2016;3(4):343 View
  6. Conway M, O’Connor D. Social media, big data, and mental health: current advances and ethical implications. Current Opinion in Psychology 2016;9:77 View
  7. Cole-Lewis H, Pugatch J, Sanders A, Varghese A, Posada S, Yun C, Schwarz M, Augustson E. Social Listening: A Content Analysis of E-Cigarette Discussions on Twitter. Journal of Medical Internet Research 2015;17(10):e243 View
  8. Huang J, Kornfield R, Szczypka G, Emery S. A cross-sectional examination of marketing of electronic cigarettes on Twitter. Tobacco Control 2014;23(suppl 3):iii26 View
  9. Zhu S, Gamst A, Lee M, Cummins S, Yin L, Zoref L, Blum A. The Use and Perception of Electronic Cigarettes and Snus among the U.S. Population. PLoS ONE 2013;8(10):e79332 View
  10. Majmundar A, Cornelis E, Moran M. Examining the vulnerability of ambivalent young adults to e-cigarette messages. Health Marketing Quarterly 2020;37(1):73 View
  11. Glasser A, Collins L, Pearson J, Abudayyeh H, Niaura R, Abrams D, Villanti A. Overview of Electronic Nicotine Delivery Systems: A Systematic Review. American Journal of Preventive Medicine 2017;52(2):e33 View
  12. Burke-Garcia A, Stanton C. A tale of two tools: Reliability and feasibility of social media measurement tools examining e-cigarette twitter mentions. Informatics in Medicine Unlocked 2017;8:8 View
  13. Thackeray R, Neiger B, Burton S, Thackeray C. Analysis of the Purpose of State Health Departments' Tweets: Information Sharing, Engagement, and Action. Journal of Medical Internet Research 2013;15(11):e255 View
  14. Zhang L, Fan H, Peng C, Rao G, Cong Q. Sentiment Analysis Methods for HPV Vaccines Related Tweets Based on Transfer Learning. Healthcare 2020;8(3):307 View
  15. Lienemann B, Unger J, Cruz T, Chu K. Methods for Coding Tobacco-Related Twitter Data: A Systematic Review. Journal of Medical Internet Research 2017;19(3):e91 View
  16. Paul M, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1 View
  17. Mowery D, Smith H, Cheney T, Stoddard G, Coppersmith G, Bryan C, Conway M. Understanding Depressive Symptoms and Psychosocial Stressors on Twitter: A Corpus-Based Study. Journal of Medical Internet Research 2017;19(2):e48 View
  18. Cavazos-Rehg P, Krauss M, Sowles S, Bierut L. Marijuana-Related Posts on Instagram. Prevention Science 2016;17(6):710 View
  19. Liu J, Ho M, Lu L, Xiao G. Recent Themes in Social Networking Service Research. PLOS ONE 2017;12(1):e0170293 View
  20. Ashford R, Curtis B. Commentary on Cohn and Colleagues: Discussions of Alcohol Use in an Online Social Network for Smoking Cessation: Analysis of Topics, Sentiment, and Social Network Centrality (ACER, 2019). Alcoholism: Clinical and Experimental Research 2019;43(3):401 View
  21. Colditz J, Welling J, Smith N, James A, Primack B. World Vaping Day: Contextualizing Vaping Culture in Online Social Media Using a Mixed Methods Approach. Journal of Mixed Methods Research 2019;13(2):196 View
  22. Hart K, Perlis R, McCoy T. What do patients learn about psychotropic medications on the web? A natural language processing study. Journal of Affective Disorders 2020;260:366 View
  23. Daniulaityte R, Chen L, Lamy F, Carlson R, Thirunarayan K, Sheth A. “When ‘Bad’ is ‘Good’”: Identifying Personal Communication and Sentiment in Drug-Related Tweets. JMIR Public Health and Surveillance 2016;2(2):e162 View
  24. Chan B, Lopez A, Sarkar U, Hildt E. The Canary in the Coal Mine Tweets: Social Media Reveals Public Perceptions of Non-Medical Use of Opioids. PLOS ONE 2015;10(8):e0135072 View
  25. Kendra R, Karki S, Eickholt J, Gandy L. Characterizing the Discussion of Antibiotics in the Twittersphere: What is the Bigger Picture?. Journal of Medical Internet Research 2015;17(6):e154 View
  26. Allem J, Dharmapuri L, Leventhal A, Unger J, Boley Cruz T. Hookah-Related Posts to Twitter From 2017 to 2018: Thematic Analysis. Journal of Medical Internet Research 2018;20(11):e11669 View
  27. Mullins C, ffrench-O'Carroll R, Lane J, O'Connor T. Sharing the pain: an observational analysis of Twitter and pain in Ireland. Regional Anesthesia & Pain Medicine 2020;45(8):597 View
  28. Nascimento T, DosSantos M, Danciu T, DeBoer M, van Holsbeeck H, Lucas S, Aiello C, Khatib L, Bender M, Zubieta J, DaSilva A. Real-Time Sharing and Expression of Migraine Headache Suffering on Twitter: A Cross-Sectional Infodemiology Study. Journal of Medical Internet Research 2014;16(4):e96 View
  29. Visweswaran S, Colditz J, O’Halloran P, Han N, Taneja S, Welling J, Chu K, Sidani J, Primack B. Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study. Journal of Medical Internet Research 2020;22(8):e17478 View
  30. Rose S, Jo C, Binns S, Buenger M, Emery S, Ribisl K. Perceptions of Menthol Cigarettes Among Twitter Users: Content and Sentiment Analysis. Journal of Medical Internet Research 2017;19(2):e56 View
  31. Doan S, Ritchart A, Perry N, Chaparro J, Conway M. How Do You #relax When You’re #stressed? A Content Analysis and Infodemiology Study of Stress-Related Tweets. JMIR Public Health and Surveillance 2017;3(2):e35 View
  32. Sabus C, Johns B, Schultz N, Gagnon K. Exploration of Content and Reach of Physical Therapy-Related Discussion on Twitter. Physical Therapy 2019;99(8):1048 View
  33. Cortese D, Szczypka G, Emery S, Wang S, Hair E, Vallone D. Smoking Selfies: Using Instagram to Explore Young Women’s Smoking Behaviors. Social Media + Society 2018;4(3) View
  34. Kim M, Kim J, Kim S, Jeong J. Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate: Machine Learning Study. Journal of Medical Internet Research 2020;22(2):e16466 View
  35. Chu K, Colditz J, Malik M, Yates T, Primack B. Identifying Key Target Audiences for Public Health Campaigns: Leveraging Machine Learning in the Case of Hookah Tobacco Smoking. Journal of Medical Internet Research 2019;21(7):e12443 View
  36. Allem J, Chu K, Cruz T, Unger J. Waterpipe Promotion and Use on Instagram: #Hookah. Nicotine & Tobacco Research 2017:ntw329 View
  37. Park A, Conway M, Chen A. Examining thematic similarity, difference, and membership in three online mental health communities from reddit: A text mining and visualization approach. Computers in Human Behavior 2018;78:98 View
  38. Kamiński M, Muth A, Bogdański P. Smoking, Vaping, and Tobacco Industry During COVID-19 Pandemic: Twitter Data Analysis. Cyberpsychology, Behavior, and Social Networking 2020;23(12):811 View
  39. Little R, West B, Boonstra P, Hu J. Measures of the Degree of Departure from Ignorable Sample Selection. Journal of Survey Statistics and Methodology 2020;8(5):932 View
  40. Kelley D, Brown M, Murray A, Blake K. Prevalence and Characteristics of Twitter Posts About Court-Ordered, Tobacco-Related Corrective Statements: Descriptive Content Analysis. JMIR Public Health and Surveillance 2019;5(4):e12878 View
  41. Chu K, Colditz J, Sidani J, Zimmer M, Primack B. Re-evaluating standards of human subjects protection for sensitive health data in social media networks. Social Networks 2021;67:41 View
  42. Lazard A, Saffer A, Wilcox G, Chung A, Mackert M, Bernhardt J. E-Cigarette Social Media Messages: A Text Mining Analysis of Marketing and Consumer Conversations on Twitter. JMIR Public Health and Surveillance 2016;2(2):e171 View
  43. Gohil S, Vuik S, Darzi A. Sentiment Analysis of Health Care Tweets: Review of the Methods Used. JMIR Public Health and Surveillance 2018;4(2):e43 View
  44. Akl E, Ward K, Bteddini D, Khaliel R, Alexander A, Lotfi T, Alaouie H, Afifi R. The allure of the waterpipe: a narrative review of factors affecting the epidemic rise in waterpipe smoking among young persons globally. Tobacco Control 2015;24(Suppl 1):i13 View
  45. Chen A, Zhu S, Conway M. What Online Communities Can Tell Us About Electronic Cigarettes and Hookah Use: A Study Using Text Mining and Visualization Techniques. Journal of Medical Internet Research 2015;17(9):e220 View
  46. Nguyen Q, Li D, Meng H, Kath S, Nsoesie E, Li F, Wen M. Building a National Neighborhood Dataset From Geotagged Twitter Data for Indicators of Happiness, Diet, and Physical Activity. JMIR Public Health and Surveillance 2016;2(2):e158 View
  47. Finfgeld-Connett D. Twitter and Health Science Research. Western Journal of Nursing Research 2015;37(10):1269 View
  48. Nguyen Q, McCullough M, Meng H, Paul D, Li D, Kath S, Loomis G, Nsoesie E, Wen M, Smith K, Li F. Geotagged US Tweets as Predictors of County-Level Health Outcomes, 2015–2016. American Journal of Public Health 2017;107(11):1776 View
  49. Nguyen J, Gilbert L, Priede L, Heckman C. The Reach of the “Don’t Fry Day” Twitter Campaign: Content Analysis. JMIR Dermatology 2019;2(1):e14137 View
  50. Kim Y, Huang J, Emery S. Garbage in, Garbage Out: Data Collection, Quality Assessment and Reporting Standards for Social Media Data Use in Health Research, Infodemiology and Digital Disease Detection. Journal of Medical Internet Research 2016;18(2):e41 View
  51. Petersen C, Halter R, Kotz D, Loeb L, Cook S, Pidgeon D, Christensen B, Batsis J. Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study. JMIR mHealth and uHealth 2020;8(8):e16862 View
  52. Mikal J, Hurst S, Conway M. Ethical issues in using Twitter for population-level depression monitoring: a qualitative study. BMC Medical Ethics 2016;17(1) View
  53. Doan S, Yang E, Tilak S, Li P, Zisook D, Torii M. Extracting health-related causality from twitter messages using natural language processing. BMC Medical Informatics and Decision Making 2019;19(S3) View
  54. Krauss M, Sowles S, Moreno M, Zewdie K, Grucza R, Bierut L, Cavazos-Rehg P. Hookah-Related Twitter Chatter: A Content Analysis. Preventing Chronic Disease 2015;12 View
  55. Ahmed S, Jaidka K, Cho J. The 2014 Indian elections on Twitter: A comparison of campaign strategies of political parties. Telematics and Informatics 2016;33(4):1071 View
  56. Allem J, Ramanujam J, Lerman K, Chu K, Boley Cruz T, Unger J. Identifying Sentiment of Hookah-Related Posts on Twitter. JMIR Public Health and Surveillance 2017;3(4):e74 View
  57. Escobedo P, Cruz T, Tsai K, Allem J, Soto D, Kirkpatrick M, Pattarroyo M, Unger J. Monitoring Tobacco Brand Websites to Understand Marketing Strategies Aimed at Tobacco Product Users and Potential Users. Nicotine & Tobacco Research 2018;20(11):1393 View
  58. Alotaibi S, Mehmood R, Katib I, Rana O, Albeshri A. Sehaa: A Big Data Analytics Tool for Healthcare Symptoms and Diseases Detection Using Twitter, Apache Spark, and Machine Learning. Applied Sciences 2020;10(4):1398 View
  59. Benson R, Hu M, Chen A, Nag S, Zhu S, Conway M. Investigating the Attitudes of Adolescents and Young Adults Towards JUUL: Computational Study Using Twitter Data. JMIR Public Health and Surveillance 2020;6(3):e19975 View
  60. Shutler L, Nelson L, Portelli I, Blachford C, Perrone J. Drug Use in the Twittersphere: A Qualitative Contextual Analysis of Tweets About Prescription Drugs. Journal of Addictive Diseases 2015;34(4):303 View
  61. Chung J. A Smoking Cessation Campaign on Twitter: Understanding the Use of Twitter and Identifying Major Players in a Health Campaign. Journal of Health Communication 2016;21(5):517 View
  62. Alghamdi A, Abumelha K, Allarakia J, Al-Shehri A. Conversations and Misconceptions About Chemotherapy in Arabic Tweets: Content Analysis. Journal of Medical Internet Research 2020;22(7):e13979 View
  63. Kim K, Gibson L, Williams S, Kim Y, Binns S, Emery S, Hornik R. Valence of Media Coverage About Electronic Cigarettes and Other Tobacco Products From 2014 to 2017: Evidence From Automated Content Analysis. Nicotine & Tobacco Research 2020;22(10):1891 View
  64. Cawkwell P, Lee L, Weitzman M, Sherman S. Tracking Hookah Bars in New York: Utilizing Yelp as a Powerful Public Health Tool. JMIR Public Health and Surveillance 2015;1(2):e19 View
  65. Foufi V, Timakum T, Gaudet-Blavignac C, Lovis C, Song M. Mining of Textual Health Information from Reddit: Analysis of Chronic Diseases With Extracted Entities and Their Relations. Journal of Medical Internet Research 2019;21(6):e12876 View
  66. Fogel J, Travis Y. Twitter use related to reality television characters: Association with increased marijuana use. Journal of Organizational Computing and Electronic Commerce 2017;27(2):152 View
  67. Haddad L, El-Shahawy O, Ghadban R, Barnett T, Johnson E. Waterpipe Smoking and Regulation in the United States: A Comprehensive Review of the Literature. International Journal of Environmental Research and Public Health 2015;12(6):6115 View
  68. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  69. Cole-Lewis H, Varghese A, Sanders A, Schwarz M, Pugatch J, Augustson E. Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning. Journal of Medical Internet Research 2015;17(8):e208 View
  70. Young S. Behavioral insights on big data: using social media for predicting biomedical outcomes. Trends in Microbiology 2014;22(11):601 View
  71. Gibson L, Siegel L, Kranzler E, Volinsky A, O’Donnell M, Williams S, Yang Q, Kim Y, Binns S, Tran H, Maidel Epstein V, Leffel T, Jeong M, Liu J, Lee S, Emery S, Hornik R. Combining Crowd-Sourcing and Automated Content Methods to Improve Estimates of Overall Media Coverage: Theme Mentions in E-cigarette and Other Tobacco Coverage. Journal of Health Communication 2019;24(12):889 View
  72. Conway M. Ethical Issues in Using Twitter for Public Health Surveillance and Research: Developing a Taxonomy of Ethical Concepts From the Research Literature. Journal of Medical Internet Research 2014;16(12):e290 View
  73. Fogel J, Shlivko A. Reality Television Programs Are Associated With Illegal Drug Use and Prescription Drug Misuse Among College Students. Substance Use & Misuse 2016;51(1):62 View
  74. Kolliakou A, Ball M, Derczynski L, Chandran D, Gkotsis G, Deluca P, Jackson R, Shetty H, Stewart R. Novel psychoactive substances: An investigation of temporal trends in social media and electronic health records. European Psychiatry 2016;38:15 View
  75. Nguyen Q, Meng H, Li D, Kath S, McCullough M, Paul D, Kanokvimankul P, Nguyen T, Li F. Social media indicators of the food environment and state health outcomes. Public Health 2017;148:120 View
  76. McCoy T, Castro V, Cagan A, Roberson A, Kohane I, Perlis R, Ramagopalan S. Sentiment Measured in Hospital Discharge Notes Is Associated with Readmission and Mortality Risk: An Electronic Health Record Study. PLOS ONE 2015;10(8):e0136341 View
  77. Allem J, Dharmapuri L, Unger J, Cruz T. Characterizing JUUL-related posts on Twitter. Drug and Alcohol Dependence 2018;190:1 View
  78. Kim A, Hopper T, Simpson S, Nonnemaker J, Lieberman A, Hansen H, Guillory J, Porter L. Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study. Journal of Medical Internet Research 2015;17(11):e251 View
  79. Tofighi B, Aphinyanaphongs Y, Marini C, Ghassemlou S, Nayebvali P, Metzger I, Raghunath A, Thomas S. Detecting illicit opioid content on Twitter. Drug and Alcohol Review 2020;39(3):205 View
  80. Waudby-Smith I, Tran N, Dubin J, Lee J, van Bogaert P. Sentiment in nursing notes as an indicator of out-of-hospital mortality in intensive care patients. PLOS ONE 2018;13(6):e0198687 View
  81. Sznitman S. Analysing Twitter as an Opportunity to Understand Substance Use. SSRN Electronic Journal 2015 View
  82. Haynes E, Garside R, Green J, Kelly M, Thomas J, Guell C. Semiautomated text analytics for qualitative data synthesis. Research Synthesis Methods 2019;10(3):452 View
  83. Hu H, Phan N, Chun S, Geller J, Vo H, Ye X, Jin R, Ding K, Kenne D, Dou D. An insight analysis and detection of drug-abuse risk behavior on Twitter with self-taught deep learning. Computational Social Networks 2019;6(1) View
  84. Alvaro N, Conway M, Doan S, Lofi C, Overington J, Collier N. Crowdsourcing Twitter annotations to identify first-hand experiences of prescription drug use. Journal of Biomedical Informatics 2015;58:280 View
  85. dos Santos B, Steiner M, Fenerich A, Lima R. Data mining and machine learning techniques applied to public health problems: A bibliometric analysis from 2009 to 2018. Computers & Industrial Engineering 2019;138:106120 View
  86. Kim Y, Kim J. Using photos for public health communication: A computational analysis of the Centers for Disease Control and Prevention Instagram photos and public responses. Health Informatics Journal 2020;26(3):2159 View
  87. Gerds A, Chan T. Social Media in Hematology in 2017: Dystopia, Utopia, or Somewhere In-between?. Current Hematologic Malignancy Reports 2017;12(6):582 View
  88. Payne J, Orellana-Barrios M, Medrano-Juarez R, Buscemi D, Nugent K. Electronic Cigarettes in the Media. Baylor University Medical Center Proceedings 2016;29(3):280 View
  89. Kandadai V, Yang H, Jiang L, Yang C, Fleisher L, Winston F. Measuring Health Information Dissemination and Identifying Target Interest Communities on Twitter: Methods Development and Case Study of the @SafetyMD Network. JMIR Research Protocols 2016;5(2):e50 View
  90. Hamad E, Savundranayagam M, Holmes J, Kinsella E, Johnson A. Toward a Mixed-Methods Research Approach to Content Analysis in The Digital Age: The Combined Content-Analysis Model and its Applications to Health Care Twitter Feeds. Journal of Medical Internet Research 2016;18(3):e60 View
  91. Ayers J, Leas E, Allem J, Benton A, Dredze M, Althouse B, Cruz T, Unger J, Olson D. Why do people use electronic nicotine delivery systems (electronic cigarettes)? A content analysis of Twitter, 2012-2015. PLOS ONE 2017;12(3):e0170702 View
  92. Chu K, Allem J, Cruz T, Unger J. Vaping on Instagram: cloud chasing, hand checks and product placement. Tobacco Control 2017;26(5):575 View
  93. Groves R. "Can I Profit from My Own Name and Likeness as a College Athlete?": The Predictive Legal Analytics of a College Player's Publicity Rights vs. First Amendment Rights of Others. Indiana Law Review 2015;48(2):369 View
  94. Buente W, Dalisay F, Pokhrel P, Kramer H, Pagano I. An Instagram-Based Study to Understand Betel Nut Use Culture in Micronesia: Exploratory Content Analysis. Journal of Medical Internet Research 2020;22(7):e13954 View
  95. Primack B, Carroll M, Shensa A, Davis W, Levine M. Sex Differences in Hookah-Related Images Posted on Tumblr: A Content Analysis. Journal of Health Communication 2016;21(3):366 View
  96. R. Scott K, Nelson L, Meisel Z, Perrone J. Opportunities for Exploring and Reducing Prescription Drug Abuse Through Social Media. Journal of Addictive Diseases 2015;34(2-3):178 View
  97. Pechmann C, Delucchi K, Lakon C, Prochaska J. Randomised controlled trial evaluation of Tweet2Quit: a social network quit-smoking intervention. Tobacco Control 2017;26(2):188 View
  98. Cavazos-Rehg P, Krauss M, Fisher S, Salyer P, Grucza R, Bierut L. Twitter Chatter About Marijuana. Journal of Adolescent Health 2015;56(2):139 View
  99. Meng H, Kath S, Li D, Nguyen Q, Giraud-Carrier C. National substance use patterns on Twitter. PLOS ONE 2017;12(11):e0187691 View
  100. Conway M, Khojoyan A, Fana F, Scuba W, Castine M, Mowery D, Chapman W, Jupp S. Developing a web-based SKOS editor. Journal of Biomedical Semantics 2016;7(1) View
  101. Allem J, Ferrara E, Uppu S, Cruz T, Unger J. E-Cigarette Surveillance With Social Media Data: Social Bots, Emerging Topics, and Trends. JMIR Public Health and Surveillance 2017;3(4):e98 View
  102. Martinez L, Hughes S, Walsh-Buhi E, Tsou M. “Okay, We Get It. You Vape”: An Analysis of Geocoded Content, Context, and Sentiment regarding E-Cigarettes on Twitter. Journal of Health Communication 2018;23(6):550 View
  103. Toloza F, Espinoza Suarez N, El Kawkgi O, Golembiewski E, Ponce O, Yao L, Maraka S, Singh Ospina N, Brito J. Patient Experiences and Perceptions Associated with the Use of Desiccated Thyroid Extract. Medicina 2020;56(4):161 View
  104. Cavazos-Rehg P, Krauss M, Grucza R, Bierut L. Characterizing the Followers and Tweets of a Marijuana-Focused Twitter Handle. Journal of Medical Internet Research 2014;16(6):e157 View
  105. Lazard A, Wilcox G, Tuttle H, Glowacki E, Pikowski J. Public reactions to e-cigarette regulations on Twitter: a text mining analysis. Tobacco Control 2017;26(e2):e112 View
  106. Pechmann C, Pan L, Delucchi K, Lakon C, Prochaska J. Development of a Twitter-Based Intervention for Smoking Cessation that Encourages High-Quality Social Media Interactions via Automessages. Journal of Medical Internet Research 2015;17(2):e50 View
  107. Dijkstra S, Kok G, Ledford J, Sandalova E, Stevelink R. Possibilities and Pitfalls of Social Media for Translational Medicine. Frontiers in Medicine 2018;5 View
  108. Dwyer R, Fraser S. Addicting via Hashtags. Contemporary Drug Problems 2016;43(1):79 View
  109. Hébert E, Case K, Kelder S, Delk J, Perry C, Harrell M. Exposure and Engagement With Tobacco- and E-Cigarette–Related Social Media. Journal of Adolescent Health 2017;61(3):371 View
  110. Li J, Li X, Zhu B. User opinion classification in social media: A global consistency maximization approach. Information & Management 2016;53(8):987 View
  111. Salloum R, Asfar T, Maziak W. Toward a Regulatory Framework for the Waterpipe. American Journal of Public Health 2016;106(10):1773 View
  112. Grzeça M, Becker K, Galante R. Drink2Vec: Improving the classification of alcohol-related tweets using distributional semantics and external contextual enrichment. Information Processing & Management 2020;57(6):102369 View
  113. Kavuluru R, Sabbir A. Toward automated e-cigarette surveillance: Spotting e-cigarette proponents on Twitter. Journal of Biomedical Informatics 2016;61:19 View
  114. Curtis B, Giorgi S, Buffone A, Ungar L, Ashford R, Hemmons J, Summers D, Hamilton C, Schwartz H, Emmert-Streib F. Can Twitter be used to predict county excessive alcohol consumption rates?. PLOS ONE 2018;13(4):e0194290 View
  115. Zipper S. Agricultural Research Using Social Media Data. Agronomy Journal 2018;110(1):349 View
  116. Katsuki T, Mackey T, Cuomo R. Establishing a Link Between Prescription Drug Abuse and Illicit Online Pharmacies: Analysis of Twitter Data. Journal of Medical Internet Research 2015;17(12):e280 View
  117. Nielsen R, Luengo-Oroz M, Mello M, Paz J, Pantin C, Erkkola T. Social Media Monitoring of Discrimination and HIV Testing in Brazil, 2014–2015. AIDS and Behavior 2017;21(S1):114 View
  118. Zhang Y, Allem J, Unger J, Boley Cruz T. Automated Identification of Hookahs (Waterpipes) on Instagram: An Application in Feature Extraction Using Convolutional Neural Network and Support Vector Machine Classification. Journal of Medical Internet Research 2018;20(11):e10513 View
  119. Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Information & Libraries Journal 2018;35(2):91 View
  120. Jordan S, Hovet S, Fung I, Liang H, Fu K, Tse Z. Using Twitter for Public Health Surveillance from Monitoring and Prediction to Public Response. Data 2018;4(1):6 View
  121. Zhang N, Campo S, Janz K, Eckler P, Yang J, Snetselaar L, Signorini A. Electronic Word of Mouth on Twitter About Physical Activity in the United States: Exploratory Infodemiology Study. Journal of Medical Internet Research 2013;15(11):e261 View
  122. Jiang K, Feng S, Song Q, Calix R, Gupta M, Bernard G. Identifying tweets of personal health experience through word embedding and LSTM neural network. BMC Bioinformatics 2018;19(S8) View
  123. Aramburu M, Berlanga R, Lanza I. Social Media Multidimensional Analysis for Intelligent Health Surveillance. International Journal of Environmental Research and Public Health 2020;17(7):2289 View
  124. Schwab-Reese L, Hovdestad W, Tonmyr L, Fluke J. The potential use of social media and other internet-related data and communications for child maltreatment surveillance and epidemiological research: Scoping review and recommendations. Child Abuse & Neglect 2018;85:187 View
  125. Young-Wolff K, Klebaner D, Folck B, Carter-Harris L, Salloum R, Prochaska J, Fogelberg R, Tan A. Do you vape? Leveraging electronic health records to assess clinician documentation of electronic nicotine delivery system use among adolescents and adults. Preventive Medicine 2017;105:32 View
  126. Massey P, Leader A, Yom-Tov E, Budenz A, Fisher K, Klassen A. Applying Multiple Data Collection Tools to Quantify Human Papillomavirus Vaccine Communication on Twitter. Journal of Medical Internet Research 2016;18(12):e318 View
  127. Gurajala S, Dhaniyala S, Matthews J. Understanding Public Response to Air Quality Using Tweet Analysis. Social Media + Society 2019;5(3) View
  128. Pearson J, Amato M, Papandonatos G, Zhao K, Erar B, Wang X, Cha S, Cohn A, Graham A. Exposure to positive peer sentiment about nicotine replacement therapy in an online smoking cessation community is associated with NRT use. Addictive Behaviors 2018;87:39 View
  129. Cavazos-Rehg P, Sowles S, Krauss M, Agbonavbare V, Grucza R, Bierut L. A content analysis of tweets about high-potency marijuana. Drug and Alcohol Dependence 2016;166:100 View
  130. van der Tempel J, Noormohamed A, Schwartz R, Norman C, Malas M, Zawertailo L. Vape, quit, tweet? Electronic cigarettes and smoking cessation on Twitter. International Journal of Public Health 2016;61(2):249 View
  131. Wang S, Paul M, Dredze M. Social Media as a Sensor of Air Quality and Public Response in China. Journal of Medical Internet Research 2015;17(3):e22 View
  132. Al-garadi M, Varathan K, Ravana S. Cybercrime detection in online communications: The experimental case of cyberbullying detection in the Twitter network. Computers in Human Behavior 2016;63:433 View
  133. KÜÇÜK D, ARICI N, KÜÇÜK E. Sosyal medyada otomatik halk sağlığı takibi: Güncel bir derleme. Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 2021 View
  134. Singh T, Roberts K, Cohen T, Cobb N, Wang J, Fujimoto K, Myneni S. Social Media as a Research Tool (SMaaRT) for Risky Behavior Analytics: Methodological Review. JMIR Public Health and Surveillance 2020;6(4):e21660 View
  135. Sim J, Miller P, Swarup S. Tweeting the High Line Life: A Social Media Lens on Urban Green Spaces. Sustainability 2020;12(21):8895 View
  136. Mehta N, Zhu L, Lam K, Stall N, Savage R, Read S, Wu W, Pop P, Faulkner C, Bronskill S, Rochon P. Health Forums and Twitter for Dementia Research: Opportunities and Considerations. Journal of the American Geriatrics Society 2020;68(12):2881 View
  137. Mendhe C, Henderson N, Srivastava G, Mago V. A Scalable Platform to Collect, Store, Visualize, and Analyze Big Data in Real Time. IEEE Transactions on Computational Social Systems 2021;8(1):260 View
  138. Netzel L, Heldt S, Denecke M. Analyzing Twitter communication about heavy precipitation events to improve future risk communication and disaster reduction in Germany. Urban Water Journal 2021;18(5):310 View
  139. Alnazzawi N, Fiorini N. Building a semantically annotated corpus for chronic disease complications using two document types. PLOS ONE 2021;16(3):e0247319 View
  140. Oyebode O, Lomotey R, Orji R. “I Tried to Breastfeed but…”: Exploring Factors Influencing Breastfeeding Behaviours Based on Tweets Using Machine Learning and Thematic Analysis. IEEE Access 2021;9:61074 View
  141. Lossio-Ventura J, Gonzales S, Morzan J, Alatrista-Salas H, Hernandez-Boussard T, Bian J. Evaluation of clustering and topic modeling methods over health-related tweets and emails. Artificial Intelligence in Medicine 2021;117:102096 View
  142. Shah A, Yan X, Qayyum A. Social Network Analysis of an Online Smoking Cessation Community to Identify Users’ Smoking Status. Healthcare Informatics Research 2021;27(2):116 View
  143. Sivrikaya E, Yilmaz O, Sivrikaya P. Dentist–patient communication on dental anxiety using the social media: A randomized controlled trial. Scandinavian Journal of Psychology 2021;62(6):780 View
  144. Rutherford B, Lim C, Johnson B, Cheng B, Chung J, Huang S, Sun T, Leung J, Stjepanović D, Chan G. #TurntTrending: a systematic review of substance use portrayals on social media platforms. Addiction 2023;118(2):206 View
  145. Xu Q, Yang J, Haupt M, Cai M, Nali M, Mackey T. Digital Surveillance to Identify California Alternative and Emerging Tobacco Industry Policy Influence and Mobilization on Facebook. International Journal of Environmental Research and Public Health 2021;18(21):11150 View
  146. Benson R, Hu M, Chen A, Zhu S, Conway M. Examining Cannabis, Tobacco, and Vaping Discourse on Reddit: An Exploratory Approach Using Natural Language Processing. Frontiers in Public Health 2022;9 View
  147. El-Amin S, Kinnunen J, Rimpelä A. Adolescents’ Perceptions of Harmfulness of Tobacco and Tobacco-like Products in Finland. International Journal of Environmental Research and Public Health 2022;19(3):1485 View
  148. Hassan L, Elkaref M, de Mel G, Bogdanovica I, Nenadic G. Text mining tweets on e-cigarette risks and benefits using machine learning following a vaping related lung injury outbreak in the USA. Healthcare Analytics 2022;2:100066 View
  149. Gao C, Espinoza Suarez N, Toloza F, Malaga Zuniga A, McCarthy S, Boehmer K, Yao L, Fu S, Brito J. Patients’ Perspective About the Cost of Diabetes Management: An Analysis of Online Health Communities. Mayo Clinic Proceedings: Innovations, Quality & Outcomes 2021;5(5):898 View
  150. Wu D, Kasson E, Singh A, Ren Y, Kaiser N, Huang M, Cavazos-Rehg P. Topics and Sentiment Surrounding Vaping on Twitter and Reddit During the 2019 e-Cigarette and Vaping Use–Associated Lung Injury Outbreak: Comparative Study. Journal of Medical Internet Research 2022;24(12):e39460 View
  151. Pilipiec P, Liwicki M, Bota A. Using Machine Learning for Pharmacovigilance: A Systematic Review. Pharmaceutics 2022;14(2):266 View
  152. Lane J, Habib D, Curtis B. Linguistic Methodologies to Surveil the Leading Causes of Mortality: Scoping Review of Twitter for Public Health Data. Journal of Medical Internet Research 2023;25:e39484 View
  153. Mittal R, Mittal A, Aggarwal I. Identification of affective valence of Twitter generated sentiments during the COVID-19 outbreak. Social Network Analysis and Mining 2021;11(1) View
  154. Chen J, Xue S, Xie Z, Li D. Perceptions and Discussions of Snus on Twitter: Observational Study. JMIR Medical Informatics 2022;10(8):e38174 View
  155. Fu R, Kundu A, Mitsakakis N, Elton-Marshall T, Wang W, Hill S, Bondy S, Hamilton H, Selby P, Schwartz R, Chaiton M. Machine learning applications in tobacco research: a scoping review. Tobacco Control 2023;32(1):99 View
  156. Roemmich K, Andalibi N. Data Subjects' Conceptualizations of and Attitudes Toward Automatic Emotion Recognition-Enabled Wellbeing Interventions on Social Media. Proceedings of the ACM on Human-Computer Interaction 2021;5(CSCW2):1 View
  157. Ren Y, Wu D, Singh A, Kasson E, Huang M, Cavazos-Rehg P. Automated Detection of Vaping-Related Tweets on Twitter During the 2019 EVALI Outbreak Using Machine Learning Classification. Frontiers in Big Data 2022;5 View
  158. Jeong H, Bayro A, Umesh S, Mamgain K, Lee M. Social Media Users’ Perceptions of a Wearable Mixed Reality Headset During the COVID-19 Pandemic: Aspect-Based Sentiment Analysis. JMIR Serious Games 2022;10(3):e36850 View
  159. Cui J, Wang Z, Ho S, Cambria E. Survey on sentiment analysis: evolution of research methods and topics. Artificial Intelligence Review 2023;56(8):8469 View
  160. DURMUŞOĞLU Z, KOCABEY ÇİFTÇİ P. Socio-demographic determinants of smoking: A data mining analysis of the Global Adult Tobacco Surveys. Türkiye Halk Sağlığı Dergisi 2021 View
  161. Baker W, Colditz J, Dobbs P, Mai H, Visweswaran S, Zhan J, Primack B. Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study. JMIR Medical Informatics 2022;10(7):e33678 View
  162. Wang Y, Wang G, Li H, Gong L, Wu Z. Mapping and analyzing the construction noise pollution in China using social media platforms. Environmental Impact Assessment Review 2022;97:106863 View
  163. dos Santos B, Steiner M, Lima R. Proposal of a method to classify female smokers based on data mining techniques. Computers & Industrial Engineering 2022;170:108363 View
  164. Zhou R, Tang Q, Xie Z, Li D. Public Perceptions of the Food and Drug Administration’s Proposed Rules Prohibiting Menthol Cigarettes on Twitter: Observational Study. JMIR Formative Research 2023;7:e42706 View
  165. Hu M, Benson R, Chen A, Zhu S, Conway M. Determining the prevalence of cannabis, tobacco, and vaping device mentions in online communities using natural language processing. Drug and Alcohol Dependence 2021;228:109016 View
  166. Haupt M, Xu Q, Yang J, Cai M, Mackey T. Characterizing Vaping Industry Political Influence and Mobilization on Facebook: Social Network Analysis. Journal of Medical Internet Research 2021;23(10):e28069 View
  167. Hébert E, Vandewater E, Businelle M, Harrell M, Kelder S, Perry C. Tobacco advertising exposure and product use among young adults: An ecological momentary assessment approach. Addictive Behaviors 2023;139:107601 View
  168. Pilipiec P, Samsten I, Bota A, Rocha L. Surveillance of communicable diseases using social media: A systematic review. PLOS ONE 2023;18(2):e0282101 View
  169. Kim I, Begay C, Ma H, Orozco F, Rogers C, Valente T, Unger J. E-Cigarette–Related Health Beliefs Expressed on Twitter Within the U.S.. AJPM Focus 2023;2(2):100067 View
  170. Berg C, Abroms L, Levine H, Romm K, Khayat A, Wysota C, Duan Z, Bar-Zeev Y. IQOS Marketing in the US: The Need to Study the Impact of FDA Modified Exposure Authorization, Marketing Distribution Channels, and Potential Targeting of Consumers. International Journal of Environmental Research and Public Health 2021;18(19):10551 View
  171. Thakur N. Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions. Analytics 2022;1(2):72 View
  172. Stekelenburg N, Horsham C, O’Hara M, Janda M. Using Social Media to Determine the Affective and Cognitive Components of Tweets about Sunburn. Dermatology 2020;236(2):75 View
  173. Groseclose S, Buckeridge D. Public Health Surveillance Systems: Recent Advances in Their Use and Evaluation. Annual Review of Public Health 2017;38(1):57 View
  174. Russell A, Colditz J, Barry A, Davis R, Shields S, Ortega J, Primack B. 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?”. Nicotine & Tobacco Research 2022;24(8):1193 View
  175. Kasson E, Singh A, Huang M, Wu D, Cavazos-Rehg P. Using a mixed methods approach to identify public perception of vaping risks and overall health outcomes on Twitter during the 2019 EVALI outbreak. International Journal of Medical Informatics 2021;155:104574 View
  176. Malakar K, Majumder P, Lu C. Twitterati on COVID-19 pandemic-environment linkage: Insights from mining one year of tweets. Environmental Development 2023;46:100835 View
  177. Salvatore C. Inference with non-probability samples and survey data integration: a science mapping study. METRON 2023;81(1):83 View
  178. Mankala S, Durai A, Padiyar A, Gkountouna O, Mahabir R. Understanding public discourse surrounding the impact of bitcoin on the environment in social media. GeoJournal 2023;88(4):4243 View
  179. Elkaim L, Levett J, Niazi F, Alvi M, Shlobin N, Linzey J, Robertson F, Bokhari R, Alotaibi N, Lasry O. Cervical Myelopathy and Social Media: Mixed Methods Analysis. Journal of Medical Internet Research 2023;25:e42097 View
  180. Buckley T, Egeghy P, Isaacs K, Richard A, Ring C, Sayre R, Sobus J, Thomas R, Ulrich E, Wambaugh J, Williams A. Cutting-edge computational chemical exposure research at the U.S. Environmental Protection Agency. Environment International 2023;178:108097 View
  181. Kim K. Scanned information exposure and support for tobacco regulations among US youth and young adult tobacco product users and non-users. Health Education Research 2023;38(5):426 View
  182. Walker A, LoParco C, Rossheim M, Livingston M. #Delta8: a retailer-driven increase in Delta-8 THC discussions on Twitter from 2020 to 2021. The American Journal of Drug and Alcohol Abuse 2023;49(4):491 View
  183. Yang G, King S, Lin H, Goldstein R. Emotional Expression on Social Media Support Forums for Substance Cessation: Observational Study of Text-Based Reddit Posts. Journal of Medical Internet Research 2023;25:e45267 View
  184. Thakur N, Duggal Y, Liu Z. Analyzing Public Reactions, Perceptions, and Attitudes during the MPox Outbreak: Findings from Topic Modeling of Tweets. Computers 2023;12(10):191 View
  185. Rhee J, Huang Y, Soroosh A, Alsudais S, Ni S, Kumar A, Paredes J, Li C, Timberlake D. The Marketing and Perceptions of Non-Tobacco Blunt Wraps on Twitter. Substance Use & Misuse 2024;59(4):469 View
  186. Brassel S, Brunner M, Campbell A, Power E, Togher L. Exploring Discussions About Virtual Reality on Twitter to Inform Brain Injury Rehabilitation: Content and Network Analysis. Journal of Medical Internet Research 2024;26:e45168 View
  187. Elmitwalli S, Mehegan J, Wellock G, Gallagher A, Gilmore A, Vellucci P. Topic prediction for tobacco control based on COP9 tweets using machine learning techniques. PLOS ONE 2024;19(2):e0298298 View
  188. McCausland K, Maycock B, Jancey J. The messages presented in online electronic cigarette promotions and discussions: a scoping review protocol. BMJ Open 2017;7(11):e018633 View
  189. Wu D, Shead H, Ren Y, Raynor P, Tao Y, Villanueva H, Hung P, Li X, Brookshire R, Eichelberger K, Guille C, Litwin A, Olatosi B. Uncovering the Complexity of Perinatal Polysubstance Use Disclosure Patterns on X: Mixed Methods Study. Journal of Medical Internet Research 2024;26:e53171 View
  190. Dhiman A, Yom-Tov E, Pellis L, Edelstein M, Pebody R, Hayward A, House T, Finnie T, Guzman D, Lampos V, Aldridge R, Beale S, Byrne T, Kovar J, Braithwaite I, Fragaszy E, Fong W, Geismar C, Hoskins S, Navaratnam A, Nguyen V, Patel P, Shrotri M, Yavlinsky A, Hardelid P, Wijlaars L, Nastouli E, Spyer M, Aryee A, McKendry R, Cheng T, Johnson A, Michie S, Gibbs J, Gilson R, Rodger A, Cox I. Estimating the household secondary attack rate and serial interval of COVID-19 using social media. npj Digital Medicine 2024;7(1) View
  191. Küçükali H, Erdoğan M. AI for Tobacco Control: Identifying Tobacco-Promoting Social Media Content Using Large Language Models. Nicotine and Tobacco Research 2024 View

Books/Policy Documents

  1. Khan I, Naqvi S, Alam M, Rizvi S. Big Data Analytics. View
  2. Grover P, Kar A, Dwivedi Y, Janssen M. Digital Nations – Smart Cities, Innovation, and Sustainability. View
  3. Optican A, Cavazos-Rehg P. Child and Adolescent Psychiatry and the Media. View
  4. Bibi S, Hussain S, Ahmed M, Zeb M. New Knowledge in Information Systems and Technologies. View
  5. Godea A, Caragea C, Bulgarov F, Ramisetty-Mikler S. Artificial Intelligence in Medicine. View
  6. Mayer M, Fernández-Luque L, Leis A. Participatory Health Through Social Media. View
  7. Shah G, Alfonso M, Jolani N. Public Health and Welfare. View
  8. Hu H, Phan N, Geller J, Vo H, Manasi B, Huang X, Di Lorio S, Dinh T, Chun S. Computational Data and Social Networks. View
  9. Epure E, Deneckere R, Salinesi C. Artificial Intelligence in Medicine. View
  10. Nguyen A, Pham H, Nguyen D, Tran T. Public Health Intelligence and the Internet. View
  11. Lazar J, Feng J, Hochheiser H. Research Methods in Human Computer Interaction. View
  12. Anwar M, Yuan Z. Smart Health. View
  13. Shah G, Alfonso M, Jolani N. Implications of Social Media Use in Personal and Professional Settings. View
  14. Lombi L. Clinical Handbook of Air Pollution-Related Diseases. View
  15. Amrani G, Khennou F, Chaoui N. Information and Software Technologies. View
  16. Ohki Y, Ikeda Y, Iyetomi H. Big Data Analysis on Global Community Formation and Isolation. View
  17. Yang Q, Rains S. The International Encyclopedia of Health Communication. View