Published on 02.04.15 in Vol 17, No 4 (2015): April
Works citing "The Painful Tweet: Text, Sentiment, and Community Structure Analyses of Tweets Pertaining to Pain"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.3769):
(note that this is only a small subset of citations)
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. Text-Mining of Online Discourse to Characterize the Nature of Pain in Low Back Pain. Journal of The Korean Society of Physical Medicine 2019;14(3):55
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Jayaraman PP, Forkan ARM, Morshed A, Haghighi PD, Kang Y. Healthcare 4.0: A review of frontiers in digital health. WIREs Data Mining and Knowledge Discovery 2020;10(2)
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Paul MJ, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1
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Zunic A, Corcoran P, Spasic I. Sentiment Analysis in Health and Well-Being: Systematic Review. JMIR Medical Informatics 2020;8(1):e16023
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Tougas ME, Chambers CT, Corkum P, Robillard JM, Gruzd A, Howard V, Kampen A, Boerner KE, Hundert AS. Social Media Content About Children’s Pain and Sleep: Content and Network Analysis. JMIR Pediatrics and Parenting 2018;1(2):e11193
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Delir Haghighi P, Kang Y, Buchbinder R, Burstein F, Whittle S. Investigating Subjective Experience and the Influence of Weather Among Individuals With Fibromyalgia: A Content Analysis of Twitter. JMIR Public Health and Surveillance 2017;3(1):e4
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Sewalk KC, Tuli G, Hswen Y, Brownstein JS, Hawkins JB. Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study. Journal of Medical Internet Research 2018;20(10):e10043
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Lee H, McAuley JH, Hübscher M, Allen HG, Kamper SJ, Moseley GL. Tweeting back: predicting new cases of back pain with mass social media data. Journal of the American Medical Informatics Association 2016;23(3):644
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Manganello JA, Falisi AL, Roberts KJ, Smith KC, McKenzie LB. Pediatric injury information seeking for mothers with young children: The role of health literacy and ehealth literacy. Journal of Communication in Healthcare 2016;9(3):223
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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
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Doan S, Ritchart A, Perry N, Chaparro JD, 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
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Hajiabadi M, Zare H, Bobarshad H. IEDC: An integrated approach for overlapping and non-overlapping community detection. Knowledge-Based Systems 2017;123:188
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Baumgartner P, Peiper N. Utilizing Big Data and Twitter to Discover Emergent Online Communities of Cannabis Users. Substance Abuse: Research and Treatment 2017;11:117822181771142
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Mullins CF, 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
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Kim AE, Hopper T, Simpson S, Nonnemaker J, Lieberman AJ, 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
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Peiper NC, Baumgartner PM, Chew RF, Hsieh YP, Bieler GS, Bobashev GV, Siege C, Zarkin GA. Patterns of Twitter Behavior Among Networks of Cannabis Dispensaries in California. Journal of Medical Internet Research 2017;19(7):e236
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Elphinston RA, Scotti Requena S, Angus D, de Andrade D, Freeman CR, Day MA. The Promotion of Policy Changes Restricting Access to Codeine Medicines on Twitter: What do National Pain Organizations Say?. The Journal of Pain 2020;21(7-8):881
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Metwally O, Blumberg S, Ladabaum U, Sinha SR. Using Social Media to Characterize Public Sentiment Toward Medical Interventions Commonly Used for Cancer Screening: An Observational Study. Journal of Medical Internet Research 2017;19(6):e200
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Dreisbach C, Koleck TA, Bourne PE, Bakken S. A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data. International Journal of Medical Informatics 2019;125:37
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Zhang P, Bhaskarabhatla S. How advocacy affects Twitter migraine conversations: A pilot cross-sectional survey of Northeast American “migraine” landscape on Twitter from May to June 2020. Cephalalgia Reports 2020;3:251581632097208
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Pavan Kumar C, Dhinesh Babu L. Fuzzy based feature engineering architecture for sentiment analysis of medical discussion over online social networks. Journal of Intelligent & Fuzzy Systems 2021;40(6):11749
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Johannes José Fijen L, Joaquín López González J, Treur J. An adaptive temporal-causal network model to analyse extinction of communication over time. Cognitive Systems Research 2021;68:73
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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
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Alattar F, Shaalan K. Using Artificial Intelligence to Understand What Causes Sentiment Changes on Social Media. IEEE Access 2021;9:61756
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Almorox EG, Stokes J, Morciano M. Has COVID-19 changed carer's views of health and care integration in care homes? A sentiment difference-in-difference analysis of on-line service reviews. Health Policy 2022;126(11):1117
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He L, Yin T, Zheng K. They May Not Work! An evaluation of eleven sentiment analysis tools on seven social media datasets. Journal of Biomedical Informatics 2022;132:104142
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Berger SE, Baria AT. Assessing Pain Research: A Narrative Review of Emerging Pain Methods, Their Technosocial Implications, and Opportunities for Multidisciplinary Approaches. Frontiers in Pain Research 2022;3
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Kim I, Begay C, Ma HJ, Orozco FR, Rogers CJ, Valente TW, Unger JB. E-Cigarette–Related Health Beliefs Expressed on Twitter Within the U.S.. AJPM Focus 2023;2(2):100067
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Vinod P, Sheeja S. Sentiment prediction model in social media data using beluga dodger optimization-based ensemble classifier. Social Network Analysis and Mining 2023;13(1)
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