Published on 26.05.15 in Vol 17, No 5 (2015): May
Works citing "Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.3863):
(note that this is only a small subset of citations)
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Deiner MS, Fathy C, Kim J, Niemeyer K, Ramirez D, Ackley SF, Liu F, Lietman TM, Porco TC. Facebook and Twitter vaccine sentiment in response to measles outbreaks. Health Informatics Journal 2019;25(3):1116
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Tu Y, Peng B, Wei G, Wu W. EPR system participants’ behavior: Evolutionary game and strategy simulation. Journal of Cleaner Production 2020;271:122659
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. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
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Yoo W, Choi D, Park K. The effects of SNS communication: How expressing and receiving information predict MERS-preventive behavioral intentions in South Korea. Computers in Human Behavior 2016;62:34
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Albalawi Y, Sixsmith J. Agenda Setting for Health Promotion: Exploring an Adapted Model for the Social Media Era. JMIR Public Health and Surveillance 2015;1(2):e21
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Kieh MD, Cho EM, Myles IA, Kuhn JH. Contrasting academic and lay press print coverage of the 2013-2016 Ebola Virus Disease outbreak. PLOS ONE 2017;12(6):e0179356
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Margagliotti G, Bollé T, Rossy Q. Worldwide analysis of crimes by the traces of their online media coverage: The case of jewellery store robberies. Digital Investigation 2019;31:200889
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Thomas TL, Friedman DB, Brandt HM, Spencer SM, Tanner A. Uncharted Waters: Communicating Health Risks During the 2014 West Virginia Water Crisis. Journal of Health Communication 2016;21(9):1062
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Smith RJ, Crutchley P, Schwartz HA, Ungar L, Shofer F, Padrez KA, Merchant RM. Variations in Facebook Posting Patterns Across Validated Patient Health Conditions: A Prospective Cohort Study. Journal of Medical Internet Research 2017;19(1):e7
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Tang L, Bie B, Park S, Zhi D. Social media and outbreaks of emerging infectious diseases: A systematic review of literature. American Journal of Infection Control 2018;46(9):962
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Reintjes R, Das E, Klemm C, Richardus JH, Keßler V, Ahmad A, van Boven M. “Pandemic Public Health Paradox”: Time Series Analysis of the 2009/10 Influenza A / H1N1 Epidemiology, Media Attention, Risk Perception and Public Reactions in 5 European Countries. PLOS ONE 2016;11(3):e0151258
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Barros JM, Duggan J, Rebholz-Schuhmann D. The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review. Journal of Medical Internet Research 2020;22(3):e13680
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Khan Y, Leung GJ, Belanger P, Gournis E, Buckeridge DL, Liu L, Li Y, Johnson IL. Comparing Twitter data to routine data sources in public health surveillance for the 2015 Pan/Parapan American Games: an ecological study. Canadian Journal of Public Health 2018;109(3):419
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Nic Lochlainn LM, Woudenberg T, van Lier A, Zonnenberg I, Philippi M, de Melker HE, Hahné SJ. A novel measles outbreak control strategy in the Netherlands in 2013–2014 using a national electronic immunization register: A study of early MMR uptake and its determinants. Vaccine 2017;35(43):5828
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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
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Tangherlini TR, Roychowdhury V, Glenn B, Crespi CM, Bandari R, Wadia A, Falahi M, Ebrahimzadeh E, Bastani R. “Mommy Blogs” and the Vaccination Exemption Narrative: Results From A Machine-Learning Approach for Story Aggregation on Parenting Social Media Sites. JMIR Public Health and Surveillance 2016;2(2):e166
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Tamul DJ, Martínez-Carrillo NI. Ample Sample? An Examination of the Representativeness of Themes Between Sampling Durations Generated From Keyword Searches for 12 Months of Immigration News From LexisNexis and Newspaper Websites. Journalism & Mass Communication Quarterly 2018;95(1):96
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Klinkenberg D, Hahné SJM, Woudenberg T, Wallinga J. The Reduction of Measles Transmission During School Vacations. Epidemiology 2018;29(4):562
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Radzikowski J, Stefanidis A, Jacobsen KH, Croitoru A, Crooks A, Delamater PL. The Measles Vaccination Narrative in Twitter: A Quantitative Analysis. JMIR Public Health and Surveillance 2016;2(1):e1
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Schwab-Reese LM, 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
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Gastañaduy PA, Banerjee E, DeBolt C, Bravo-Alcántara P, Samad SA, Pastor D, Rota PA, Patel M, Crowcroft NS, Durrheim DN. Public health responses during measles outbreaks in elimination settings: Strategies and challenges. Human Vaccines & Immunotherapeutics 2018;14(9):2222
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Fadda M, Allam A, Schulz PJ. Arguments and sources on Italian online forums on childhood vaccinations: Results of a content analysis. Vaccine 2015;33(51):7152
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Kim I, Feng C, Wang Y, Spitzberg BH, Tsou M. Exploratory Spatiotemporal Analysis in Risk Communication during the MERS Outbreak in South Korea. The Professional Geographer 2017;69(4):629
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Yan S, Chughtai A, Macintyre C. Utility and potential of rapid epidemic intelligence from internet-based sources. International Journal of Infectious Diseases 2017;63:77
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SHIMASAKI N, OKAUE A, KIKUNO R, SHINOHARA K. Comparison of the Filter Efficiency of Medical Nonwoven Fabrics against Three Different Microbe Aerosols. Biocontrol Science 2018;23(2):61
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Hansen ND, Mølbak K, Cox IJ, Lioma C. Relationship Between Media Coverage and Measles-Mumps-Rubella (MMR) Vaccination Uptake in Denmark: Retrospective Study. JMIR Public Health and Surveillance 2019;5(1):e9544
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Quade P, Nsoesie EO. A Platform for Crowdsourced Foodborne Illness Surveillance: Description of Users and Reports. JMIR Public Health and Surveillance 2017;3(3):e42
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Sarker A, Belousov M, Friedrichs J, Hakala K, Kiritchenko S, Mehryary F, Han S, Tran T, Rios A, Kavuluru R, de Bruijn B, Ginter F, Mahata D, Mohammad SM, Nenadic G, Gonzalez-Hernandez G. Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task. Journal of the American Medical Informatics Association 2018;25(10):1274
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Gozzi N, Tizzani M, Starnini M, Ciulla F, Paolotti D, Panisson A, Perra N. Collective Response to Media Coverage of the COVID-19 Pandemic on Reddit and Wikipedia: Mixed-Methods Analysis. Journal of Medical Internet Research 2020;22(10):e21597
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Wang T, Lu K, Chow KP, Zhu Q. COVID-19 Sensing: Negative Sentiment Analysis on Social Media in China via BERT Model. IEEE Access 2020;8:138162
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Gupta A, Katarya R. Social media based surveillance systems for healthcare using machine learning: A systematic review. Journal of Biomedical Informatics 2020;108:103500
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Rovetta A, Bhagavathula AS. COVID-19-Related Web Search Behaviors and Infodemic Attitudes in Italy: Infodemiological Study. JMIR Public Health and Surveillance 2020;6(2):e19374
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Pruss D, Fujinuma Y, Daughton AR, Paul MJ, Arnot B, Albers Szafir D, Boyd-Graber J, Xia F. Zika discourse in the Americas: A multilingual topic analysis of Twitter. PLOS ONE 2019;14(5):e0216922
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Fagerlin A, Valley TS, Scherer AM, Knaus M, Das E, Zikmund-Fisher BJ. Communicating infectious disease prevalence through graphics: Results from an international survey. Vaccine 2017;35(32):4041
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Peng W, Occa A, McFarlane SJ, Morgan SE. A Content Analysis of the Discussions about Clinical Trials on A Cancer-dedicated Online Forum. Journal of Health Communication 2019;24(12):912
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Xie T, Tan T, Li J.
An Extensive Search Trends-Based Analysis of Public Attention on Social Media in the Early Outbreak of COVID-19 in China
. Risk Management and Healthcare Policy 2020;Volume 13:1353
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Liu K, Chen L. Medical Social Media Text Classification Integrating Consumer Health Terminology. IEEE Access 2019;7:78185
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Suppli CH, Hansen ND, Rasmussen M, Valentiner-Branth P, Krause TG, Mølbak K. Decline in HPV-vaccination uptake in Denmark – the association between HPV-related media coverage and HPV-vaccination. BMC Public Health 2018;18(1)
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van Lent LG, Sungur H, Kunneman FA, van de Velde B, Das E. Too Far to Care? Measuring Public Attention and Fear for Ebola Using Twitter. Journal of Medical Internet Research 2017;19(6):e193
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Matza LS, Paulus TM, Garris CP, Van de Velde N, Chounta V, Deger KA. Qualitative Thematic Analysis of Social Media Data to Assess Perceptions of Route of Administration for Antiretroviral Treatment among People Living with HIV. The Patient - Patient-Centered Outcomes Research 2020;13(4):409
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Qiu J, Xu L, Wang J, Gu W. Mutual influences between message volume and emotion intensity on emerging infectious diseases: An investigation with microblog data. Information & Management 2020;57(4):103217
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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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Kim SC, Hawkins KH. The psychology of social media communication in influencing prevention intentions during the 2019 U.S. measles outbreak. Computers in Human Behavior 2020;111:106428
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Tang L, Bie B, Zhi D. Tweeting about measles during stages of an outbreak: A semantic network approach to the framing of an emerging infectious disease. American Journal of Infection Control 2018;46(12):1375
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Kunneman F, Lambooij M, Wong A, Bosch AVD, Mollema L. Monitoring stance towards vaccination in twitter messages. BMC Medical Informatics and Decision Making 2020;20(1)
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Bonnevie E, Goldbarg J, Gallegos-Jeffrey AK, Rosenberg SD, Wartella E, Smyser J. Content Themes and Influential Voices Within Vaccine Opposition on Twitter, 2019. American Journal of Public Health 2020;110(S3):S326
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Wicke P, Bolognesi MM, Athanasopoulos P. Framing COVID-19: How we conceptualize and discuss the pandemic on Twitter. PLOS ONE 2020;15(9):e0240010
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Postma LGM, Donyai P. The cooccurrence of heightened media attention and adverse drug reaction reports for hormonal contraception in the United Kingdom between 2014 and 2017. British Journal of Clinical Pharmacology 2021;87(4):1768
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Gencoglu O, Gruber M. Causal Modeling of Twitter Activity during COVID-19. Computation 2020;8(4):85
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. Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19. Machine Learning and Knowledge Extraction 2020;2(4):603
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Shi W, Liu D, Yang J, Zhang J, Wen S, Su J. Social Bots’ Sentiment Engagement in Health Emergencies: A Topic-Based Analysis of the COVID-19 Pandemic Discussions on Twitter. International Journal of Environmental Research and Public Health 2020;17(22):8701
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Al-Khalifa KS, AlSheikh R, Alsahafi YA, Alkhalifa A, Sadaf S, Muazen YY, Al-Moumen SA, Yermal AS. Dental care during the COVID-19 Pandemic: An Arabic tweets analysis (Preprint). JMIR Public Health and Surveillance 2020;
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Momynaliev KT, Khoperskay LL, Pshenichnaya NY, Abuova GN, Akimkin VG. Infodemiological study of coronavirus epidemic using Google Trends in Central Asian Republics of Kazakhstan, Kyrgyzstan, Uzbekistan, Tajikistan. Medical alphabet 2021;(34):47
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Karafillakis E, Martin S, Simas C, Olsson K, Takacs J, Dada S, Larson HJ. Methods for Social Media Monitoring Related to Vaccination: Systematic Scoping Review. JMIR Public Health and Surveillance 2021;7(2):e17149
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Bonnevie E, Gallegos-Jeffrey A, Goldbarg J, Byrd B, Smyser J. Quantifying the rise of vaccine opposition on Twitter during the COVID-19 pandemic. Journal of Communication in Healthcare 2021;14(1):12
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Alvarez-Galvez J, Suarez-Lledo V, Rojas-Garcia A. Determinants of Infodemics During Disease Outbreaks: A Systematic Review. Frontiers in Public Health 2021;9
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Wicke P, Bolognesi MM. Covid-19 Discourse on Twitter: How the Topics, Sentiments, Subjectivity, and Figurative Frames Changed Over Time. Frontiers in Communication 2021;6
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Nguyen TH, Le XC. How social media fosters the elders' COVID-19 preventive behaviors: perspectives of information value and perceived threat. Library Hi Tech 2021;39(3):776
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Xie R, Chu SKW, Chiu DKW, Wang Y. Exploring Public Response to COVID-19 on Weibo with LDA Topic Modeling and Sentiment Analysis. Data and Information Management 2021;5(1):86
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Gabarron E, Rivera-Romero O, Miron-Shatz T, Grainger R, Denecke K. Role of Participatory Health Informatics in Detecting and Managing Pandemics: Literature Review. Yearbook of Medical Informatics 2021;30(01):200
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Bonnevie E, Sittig J, Smyser J. The case for tracking misinformation the way we track disease. Big Data & Society 2021;8(1):205395172110138
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Bonnevie E, Goldbarg J, Gallegos-Jeffry AK, Rosenberg SD, Wartella E, Smyser J. Temas de contenido y voces influyentes dentro de la oposición a las vacunas en Twitter, 2019. Revista Panamericana de Salud Pública 2021;45:1
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Al-Khalifa KS, AlSheikh R, Alsahafi YA, Alkhalifa A, Sadaf S, Al-Moumen SA, Muazen YY, Shetty AC. Dental Care in the Arab Countries During the COVID-19 Pandemic: An Infodemiological Study. Risk Management and Healthcare Policy 2021;Volume 14:2153
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Deng W, Yang Y. Cross-Platform Comparative Study of Public Concern on Social Media during the COVID-19 Pandemic: An Empirical Study Based on Twitter and Weibo. International Journal of Environmental Research and Public Health 2021;18(12):6487
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Al-Rawi A, Grepin K, Li X, Morgan R, Wenham C, Smith J. Investigating Public Discourses Around Gender and COVID-19: a Social Media Analysis of Twitter Data. Journal of Healthcare Informatics Research 2021;5(3):249
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. Do public comments make a difference in open rulemaking? Insights from information management using machine learning and QCA analysis. Government Information Quarterly 2023;40(1):101778
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. COVID-19 dialogue on Facebook: Crisis Communication relationship between Ghanaian Authorities and Citizens. Journal of International Crisis and Risk Communication Research 2022;5(1):57
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Allen C, Andersen B, Khoury M, Roberts M. Current Social Media Conversations about Genetics and Genomics in Health: A Twitter-Based Analysis. Public Health Genomics 2018;21(1-2):93
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Izhar TAT, Torabi T. Online searching trend on Covid-19 using Google trend: infodemiological study in Malaysia. International Journal of Information Technology 2022;14(2):675
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Roe C, Lowe M, Williams B, Miller C. Public Perception of SARS-CoV-2 Vaccinations on Social Media: Questionnaire and Sentiment Analysis. International Journal of Environmental Research and Public Health 2021;18(24):13028
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Stege H, Schneider S, Forschner A, Eigentler T, Nashan D, Huening S, Meiss F, Lehr S, Kaatz M, Kuchen R, Kaehler KC, Haist M, Huebner J, Loquai C. eHealth Literacy in German Skin Cancer Patients. International Journal of Environmental Research and Public Health 2022;19(14):8365
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Chen T, Tong C, Bai Y, Yang J, Cong G, Cong T. Analysis of the Public Opinion Evolution on the Normative Policies for the Live Streaming E-Commerce Industry Based on Online Comment Mining under COVID-19 Epidemic in China. Mathematics 2022;10(18):3387
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Zhang M, Chen Z, Qi X, Liu J. Could Social Bots’ Sentiment Engagement Shape Humans’ Sentiment on COVID-19 Vaccine Discussion on Twitter?. Sustainability 2022;14(9):5566
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. Population Control, Deadly Vaccines, and Mutant Mosquitoes: The Construction and Circulation of Zika Virus Conspiracy Theories Online. Canadian Journal of Communication 2019;44(2):211
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Dong X, Lian Y. A review of social media-based public opinion analyses: Challenges and recommendations. Technology in Society 2021;67:101724
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Wang H, Shi J, Sharma K. Intermedia Agenda Setting amid the Pandemic: A Computational Analysis of China’s Online News. Computational Intelligence and Neuroscience 2022;2022:1
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Lian Y, Lin X, Dong X, Hou S. A Normalized Rich-Club Connectivity-Based Strategy for Keyword Selection in Social Media Analysis. Sustainability 2022;14(13):7722
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Shao C, Guan X, Sun J, Cole M, Liu G. Social media interactions between government and the public: A Chinese case study of government WeChat official accounts on information related to COVID-19. Frontiers in Psychology 2022;13
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Khoroshun DK, Momynaliev K, Voronin EM, Akimkin VG. Analysis of Yandex search queries related to COVID‑19 in Russian Federation. Medical alphabet 2022;(14):14
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Pratiwi H, Benkő R, Kusuma IY. Navigating the asthma network on Twitter: Insights from social network and sentiment analysis. DIGITAL HEALTH 2024;10
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.3863):
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Shin EK, Shaban-Nejad A. Public Health Intelligence and the Internet. 2017. Chapter 1:1
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Rustagi S, Patel D. Transactions on Large-Scale Data- and Knowledge-Centered Systems XLIII. 2020. Chapter 5:114
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Lee B, Jeong H, Shin EK. Explainable AI in Healthcare and Medicine. 2021. Chapter 17:187
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Novak J, Maljur T, Drenska K. HCI International 2022 – Late Breaking Papers: Interacting with eXtended Reality and Artificial Intelligence. 2022. Chapter 31:441
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Shaikh S, Yayilgan SY, Zoto E, Abomhara M. Intelligent Computing. 2022. Chapter 43:627
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Melton CA, Bae J, Olusanya OA, Brenas JH, Shin EK, Shaban-Nejad A. Multimodal AI in Healthcare. 2023. Chapter 18:257
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