Published on in Vol 17, No 2 (2015): February

Twitter Sentiment Predicts Affordable Care Act Marketplace Enrollment

Twitter Sentiment Predicts Affordable Care Act Marketplace Enrollment

Twitter Sentiment Predicts Affordable Care Act Marketplace Enrollment

Journals

  1. Hao J, Dai H. Payday Loan Marketing in Social Media Networks. Journal of Consumer Affairs 2018;52(2):441 View
  2. Xu Z, Guo H. Using Text Mining to Compare Online Pro- and Anti-Vaccine Headlines: Word Usage, Sentiments, and Online Popularity. Communication Studies 2018;69(1):103 View
  3. Mostafa M, Nebot N. Sentiment analysis of Arabic language influence on Spanish vocabulary: An El País newspaper and Twitter case study. Journal of Information Technology Case and Application Research 2017;19(3):145 View
  4. Ji R, Chen F, Cao L, Gao Y. Cross-Modality Microblog Sentiment Prediction via Bi-Layer Multimodal Hypergraph Learning. IEEE Transactions on Multimedia 2019;21(4):1062 View
  5. Hawkins J, Brownstein J, Tuli G, Runels T, Broecker K, Nsoesie E, McIver D, Rozenblum R, Wright A, Bourgeois F, Greaves F. Measuring patient-perceived quality of care in US hospitals using Twitter. BMJ Quality & Safety 2016;25(6):404 View
  6. Dai H, Lee B, Hao J. Predicting Asthma Prevalence by Linking Social Media Data and Traditional Surveys. The ANNALS of the American Academy of Political and Social Science 2017;669(1):75 View
  7. Sinnenberg L, Buttenheim A, Padrez K, Mancheno C, Ungar L, Merchant R. Twitter as a Tool for Health Research: A Systematic Review. American Journal of Public Health 2017;107(1):e1 View
  8. Xu Z. How emergency managers engage Twitter users during disasters. Online Information Review 2020;44(4):933 View
  9. Crannell W, Clark E, Jones C, James T, Moore J. A pattern-matched Twitter analysis of US cancer-patient sentiments. Journal of Surgical Research 2016;206(2):536 View
  10. Han L, Han L, Darney B, Rodriguez M. Tweeting PP: an analysis of the 2015–2016 Planned Parenthood controversy on Twitter. Contraception 2017;96(6):388 View
  11. Hao J, Dai H. Social media content and sentiment analysis on consumer security breaches. Journal of Financial Crime 2016;23(4):855 View
  12. van den Broek-Altenburg E, Atherly A. Using Social Media to Identify Consumers’ Sentiments towards Attributes of Health Insurance during Enrollment Season. Applied Sciences 2019;9(10):2035 View
  13. Gollust S, Qin X, Wilcock A, Baum L, Barry C, Niederdeppe J, Fowler E, Karaca-Mandic P. Search and You Shall Find: Geographic Characteristics Associated With Google Searches During the Affordable Care Act’s First Enrollment Period. Medical Care Research and Review 2017;74(6):723 View
  14. Pai R, Alathur S. Assessing mobile health applications with twitter analytics. International Journal of Medical Informatics 2018;113:72 View
  15. Merchant R, Asch D, Crutchley P, Ungar L, Guntuku S, Eichstaedt J, Hill S, Padrez K, Smith R, Schwartz H, Ramagopalan S. Evaluating the predictability of medical conditions from social media posts. PLOS ONE 2019;14(6):e0215476 View
  16. Seltzer E, Jean N, Kramer-Golinkoff E, Asch D, Merchant R. The content of social media's shared images about Ebola: a retrospective study. Public Health 2015;129(9):1273 View
  17. Chen F, Ji R, Su J, Cao D, Gao Y. Predicting Microblog Sentiments via Weakly Supervised Multimodal Deep Learning. IEEE Transactions on Multimedia 2018;20(4):997 View
  18. Graves R, Tufts C, Meisel Z, Polsky D, Ungar L, Merchant R. Opioid Discussion in the Twittersphere. Substance Use & Misuse 2018;53(13):2132 View
  19. Mostafa M, Nebot N. The Arab Image in Spanish Social Media: A Twitter Sentiment Analytics Approach. Journal of Intercultural Communication Research 2020;49(2):133 View
  20. Davis M, Zheng K, Liu Y, Levy H. Public Response to Obamacare on Twitter. Journal of Medical Internet Research 2017;19(5):e167 View
  21. Anwar M, Khoury D, Aldridge A, Parker S, Conway K. Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study. JMIR Public Health and Surveillance 2020;6(2):e17574 View
  22. Alzahrani A, Alghamdi A, Alqarni T, Alshareef R, Alzahrani A. Prevalence and predictors of depression, anxiety, and stress symptoms among patients with type II diabetes attending primary healthcare centers in the western region of Saudi Arabia: a cross-sectional study. International Journal of Mental Health Systems 2019;13(1) View
  23. Mostafa M. Mining and mapping halal food consumers: A geo-located Twitter opinion polarity analysis. Journal of Food Products Marketing 2018;24(7):858 View
  24. Yeung D. Social Media as a Catalyst for Policy Action and Social Change for Health and Well-Being: Viewpoint. Journal of Medical Internet Research 2018;20(3):e94 View
  25. Genie M, Loría-Rebolledo L, Paranjothy S, Powell D, Ryan M, Sakowsky R, Watson V. Understanding public preferences and trade-offs for government responses during a pandemic: a protocol for a discrete choice experiment in the UK. BMJ Open 2020;10(11):e043477 View
  26. La Regina M, Mancini A, Falli F, Fineschi V, Ramacciati N, Frati P, Tartaglia R. Aggressions on Social Networks: What Are the Implications for Healthcare Providers? An Exploratory Research. Healthcare 2021;9(7):811 View

Books/Policy Documents

  1. Dony C, Fekete E. Geospatial Technologies for Urban Health. View
  2. Marisa Ferreira Gomes C, Paula Castro Amorim M, Jorge Ferreira Rodrigues M. E-Services [Working Title]. View