Published on 23.02.15 in Vol 17, No 2 (2015): February
Works citing "Twitter Sentiment Predicts Affordable Care Act Marketplace Enrollment"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.3812):
(note that this is only a small subset of citations)
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Hao J, Dai H. Payday Loan Marketing in Social Media Networks. Journal of Consumer Affairs 2018;52(2):441
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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
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Mostafa MM, Nebot NR. 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
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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
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Hawkins JB, Brownstein JS, Tuli G, Runels T, Broecker K, Nsoesie EO, McIver DJ, Rozenblum R, Wright A, Bourgeois FT, Greaves F. Measuring patient-perceived quality of care in US hospitals using Twitter. BMJ Quality & Safety 2016;25(6):404
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Dai H, Lee BR, 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
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Sinnenberg L, Buttenheim AM, Padrez K, Mancheno C, Ungar L, Merchant RM. Twitter as a Tool for Health Research: A Systematic Review. American Journal of Public Health 2017;107(1):e1
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. How emergency managers engage Twitter users during disasters. Online Information Review 2020;44(4):933
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Crannell WC, Clark E, Jones C, James TA, Moore J. A pattern-matched Twitter analysis of US cancer-patient sentiments. Journal of Surgical Research 2016;206(2):536
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Han L, Han L, Darney B, Rodriguez MI. Tweeting PP: an analysis of the 2015–2016 Planned Parenthood controversy on Twitter. Contraception 2017;96(6):388
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Hao J, Dai H. Social media content and sentiment analysis on consumer security breaches. Journal of Financial Crime 2016;23(4):855
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van den Broek-Altenburg EM, Atherly AJ. Using Social Media to Identify Consumers’ Sentiments towards Attributes of Health Insurance during Enrollment Season. Applied Sciences 2019;9(10):2035
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Gollust SE, Qin X, Wilcock AD, Baum LM, Barry CL, Niederdeppe J, Fowler EF, 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
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Pai RR, Alathur S. Assessing mobile health applications with twitter analytics. International Journal of Medical Informatics 2018;113:72
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Merchant RM, Asch DA, Crutchley P, Ungar LH, Guntuku SC, Eichstaedt JC, Hill S, Padrez K, Smith RJ, Schwartz HA, Ramagopalan SV. Evaluating the predictability of medical conditions from social media posts. PLOS ONE 2019;14(6):e0215476
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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
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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
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Graves RL, Tufts C, Meisel ZF, Polsky D, Ungar L, Merchant RM. Opioid Discussion in the Twittersphere. Substance Use & Misuse 2018;53(13):2132
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Mostafa MM, Nebot NR. The Arab Image in Spanish Social Media: A Twitter Sentiment Analytics Approach. Journal of Intercultural Communication Research 2020;49(2):133
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Davis MA, Zheng K, Liu Y, Levy H. Public Response to Obamacare on Twitter. Journal of Medical Internet Research 2017;19(5):e167
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Anwar M, Khoury D, Aldridge AP, Parker SJ, Conway KP. Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study. JMIR Public Health and Surveillance 2020;6(2):e17574
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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)
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. Mining and mapping halal food consumers: A geo-located Twitter opinion polarity analysis. Journal of Food Products Marketing 2018;24(7):858
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. 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
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Genie MG, Loría-Rebolledo LE, Paranjothy S, Powell D, Ryan M, Sakowsky RA, 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
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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
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Gour A, Aggarwal S, Kumar S. Lending ears to unheard voices: An empirical analysis of user‐generated content on social media. Production and Operations Management 2022;31(6):2457
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Gratz O, Vos D, Burke M, Soares N. Assessment of Agreement Between Human Ratings and Lexicon-Based Sentiment Ratings of Open-Ended Responses on a Behavioral Rating Scale. Assessment 2022;29(5):1075
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Eberth JM, Kramer MR, Delmelle EM, Kirby RS. What is the place for space in epidemiology?. Annals of Epidemiology 2021;64:41
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Swanson K, Ravi A, Saleh S, Weia B, Pleasants E, Arvisais-Anhalt S. Effect of Recent Abortion Legislation on Twitter User Engagement, Sentiment, and Expressions of Trust in Clinicians and Privacy of Health Information: Content Analysis. Journal of Medical Internet Research 2023;25:e46655
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Cero I, Luo J, Falligant JM. Lexicon-Based Sentiment Analysis in Behavioral Research. Perspectives on Behavior Science 2024;47(1):283
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.3812):