Published on in Vol 15, No 11 (2013): November

Electronic Word of Mouth on Twitter About Physical Activity in the United States: Exploratory Infodemiology Study

Electronic Word of Mouth on Twitter About Physical Activity in the United States: Exploratory Infodemiology Study

Electronic Word of Mouth on Twitter About Physical Activity in the United States: Exploratory Infodemiology Study

Journals

  1. Cesare N, Dwivedi P, Nguyen Q, Nsoesie E. Use of social media, search queries, and demographic data to assess obesity prevalence in the United States. Palgrave Communications 2019;5(1) View
  2. Zhang N, Campo S, Yang J, Eckler P, Snetselaar L, Janz K, Leary E. What Motivates Young Adults to Talk About Physical Activity on Social Network Sites?. Journal of Medical Internet Research 2017;19(6):e226 View
  3. 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
  4. Huang D, Huang Y, Khanna S, Dwivedi P, Slopen N, Green K, He X, Puett R, Nguyen Q. Twitter-Derived Social Neighborhood Characteristics and Individual-Level Cardiometabolic Outcomes: Cross-Sectional Study in a Nationally Representative Sample. JMIR Public Health and Surveillance 2020;6(3):e17969 View
  5. Timmins K, Green M, Radley D, Morris M, Pearce J. How has big data contributed to obesity research? A review of the literature. International Journal of Obesity 2018;42(12):1951 View
  6. Middleton L, Hall H, Raeside R. Applications and applicability of Social Cognitive Theory in information science research. Journal of Librarianship and Information Science 2019;51(4):927 View
  7. 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
  8. Sullivan L, Harvey H, Smith G, Yang J. Putting Policy Into Practice. Journal of Public Health Management and Practice 2020;26:S84 View
  9. Liu J, Ho M, Lu L, Xiao G. Recent Themes in Social Networking Service Research. PLOS ONE 2017;12(1):e0170293 View
  10. Paul M, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1 View
  11. Coxe K, Hamilton K, Harvey H, Xiang J, Ramirez M, Yang J. Consistency and Variation in School-Level Youth Sports Traumatic Brain Injury Policy Content. Journal of Adolescent Health 2018;62(3):255 View
  12. 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
  13. 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
  14. 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
  15. 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
  16. Nguyen Q, Kath S, Meng H, Li D, Smith K, VanDerslice J, Wen M, Li F. Leveraging geotagged Twitter data to examine neighborhood happiness, diet, and physical activity. Applied Geography 2016;73:77 View
  17. Gurajala S, Dhaniyala S, Matthews J. Understanding Public Response to Air Quality Using Tweet Analysis. Social Media + Society 2019;5(3):205630511986765 View
  18. 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
  19. Zhang N, Drake S, Ding K. Message Appeals on an Instagram Account Promoting Seat Belt Use That Attract Adolescents and Young Adults: Elaboration-Likelihood Perspective Study. JMIR Formative Research 2020;4(9):e16800 View
  20. Reavley N, Pilkington P. Use of Twitter to monitor attitudes toward depression and schizophrenia: an exploratory study. PeerJ 2014;2:e647 View
  21. McClellan C, Ali M, Mutter R, Kroutil L, Landwehr J. Using social media to monitor mental health discussions − evidence from Twitter. Journal of the American Medical Informatics Association 2017;24(3):496 View
  22. Drake S, Zhang N, Applewhite C, Fowler K, Holcomb J. A social media program to increase adolescent seat belt use. Public Health Nursing 2017;34(5):500 View
  23. Nguyen Q, Brunisholz K, Yu W, McCullough M, Hanson H, Litchman M, Li F, Wan Y, VanDerslice J, Wen M, Smith K. Twitter-derived neighborhood characteristics associated with obesity and diabetes. Scientific Reports 2017;7(1) View
  24. Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Information & Libraries Journal 2018;35(2):91 View
  25. Pinkerton S, Tobin J, Querfurth S, Pena I, Wilson K. “Those sweet, sweet likes”: Sharing physical activity over social network sites. Computers in Human Behavior 2017;69:128 View
  26. 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