Published on in Vol 17, No 5 (2015): May

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

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

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

Journals

  1. Deiner M, Fathy C, Kim J, Niemeyer K, Ramirez D, Ackley S, Liu F, Lietman T, Porco T. Facebook and Twitter vaccine sentiment in response to measles outbreaks. Health Informatics Journal 2019;25(3):1116 View
  2. Saleh S, Lehmann C, McDonald S, Basit M, Medford R. Understanding public perception of coronavirus disease 2019 (COVID-19) social distancing on Twitter. Infection Control & Hospital Epidemiology 2021;42(2):131 View
  3. Tu Y, Peng B, Wei G, Wu W. EPR system participants’ behavior: Evolutionary game and strategy simulation. Journal of Cleaner Production 2020;271:122659 View
  4. Becker B, Larson H, Bonhoeffer J, van Mulligen E, Kors J, Sturkenboom M. Evaluation of a multinational, multilingual vaccine debate on Twitter. Vaccine 2016;34(50):6166 View
  5. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  6. 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 View
  7. 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 View
  8. Kieh M, Cho E, Myles I, Kuhn J. Contrasting academic and lay press print coverage of the 2013-2016 Ebola Virus Disease outbreak. PLOS ONE 2017;12(6):e0179356 View
  9. 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 View
  10. Thomas T, Friedman D, Brandt H, Spencer S, Tanner A. Uncharted Waters: Communicating Health Risks During the 2014 West Virginia Water Crisis. Journal of Health Communication 2016;21(9):1062 View
  11. Smith R, Crutchley P, Schwartz H, Ungar L, Shofer F, Padrez K, Merchant R. Variations in Facebook Posting Patterns Across Validated Patient Health Conditions: A Prospective Cohort Study. Journal of Medical Internet Research 2017;19(1):e7 View
  12. 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 View
  13. Reintjes R, Das E, Klemm C, Richardus J, 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 View
  14. Barros J, 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 View
  15. Khan Y, Leung G, Belanger P, Gournis E, Buckeridge D, Liu L, Li Y, Johnson I. 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 View
  16. Nic Lochlainn L, Woudenberg T, van Lier A, Zonnenberg I, Philippi M, de Melker H, Hahné S. 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 View
  17. 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
  18. Tangherlini T, Roychowdhury V, Glenn B, Crespi C, 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 View
  19. Tamul D, Martínez-Carrillo N. 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 View
  20. Klinkenberg D, Hahné S, Woudenberg T, Wallinga J. The Reduction of Measles Transmission During School Vacations. Epidemiology 2018;29(4):562 View
  21. Radzikowski J, Stefanidis A, Jacobsen K, Croitoru A, Crooks A, Delamater P. The Measles Vaccination Narrative in Twitter: A Quantitative Analysis. JMIR Public Health and Surveillance 2016;2(1):e1 View
  22. Schwab-Reese L, 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 View
  23. Gastañaduy P, Banerjee E, DeBolt C, Bravo-Alcántara P, Samad S, Pastor D, Rota P, Patel M, Crowcroft N, Durrheim D. Public health responses during measles outbreaks in elimination settings: Strategies and challenges. Human Vaccines & Immunotherapeutics 2018;14(9):2222 View
  24. Fadda M, Allam A, Schulz P. Arguments and sources on Italian online forums on childhood vaccinations: Results of a content analysis. Vaccine 2015;33(51):7152 View
  25. Kim I, Feng C, Wang Y, Spitzberg B, Tsou M. Exploratory Spatiotemporal Analysis in Risk Communication during the MERS Outbreak in South Korea. The Professional Geographer 2017;69(4):629 View
  26. 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 View
  27. 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 View
  28. Hansen N, Mølbak K, Cox I, 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 View
  29. Quade P, Nsoesie E. A Platform for Crowdsourced Foodborne Illness Surveillance: Description of Users and Reports. JMIR Public Health and Surveillance 2017;3(3):e42 View
  30. 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 S, 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 View
  31. 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 View
  32. Wang T, Lu K, Chow K, Zhu Q. COVID-19 Sensing: Negative Sentiment Analysis on Social Media in China via BERT Model. IEEE Access 2020;8:138162 View
  33. Gupta A, Katarya R. Social media based surveillance systems for healthcare using machine learning: A systematic review. Journal of Biomedical Informatics 2020;108:103500 View
  34. Rovetta A, Bhagavathula A. COVID-19-Related Web Search Behaviors and Infodemic Attitudes in Italy: Infodemiological Study. JMIR Public Health and Surveillance 2020;6(2):e19374 View
  35. Pruss D, Fujinuma Y, Daughton A, Paul M, 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 View
  36. Fagerlin A, Valley T, Scherer A, Knaus M, Das E, Zikmund-Fisher B. Communicating infectious disease prevalence through graphics: Results from an international survey. Vaccine 2017;35(32):4041 View
  37. Peng W, Occa A, McFarlane S, Morgan S. A Content Analysis of the Discussions about Clinical Trials on A Cancer-dedicated Online Forum. Journal of Health Communication 2019;24(12):912 View
  38. Xie T, Tan T, Li J. <p>An Extensive Search Trends-Based Analysis of Public Attention on Social Media in the Early Outbreak of COVID-19 in China</p>. Risk Management and Healthcare Policy 2020;Volume 13:1353 View
  39. Liu K, Chen L. Medical Social Media Text Classification Integrating Consumer Health Terminology. IEEE Access 2019;7:78185 View
  40. Suppli C, Hansen N, Rasmussen M, Valentiner-Branth P, Krause T, 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) View
  41. van Lent L, Sungur H, Kunneman F, 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 View
  42. Matza L, Paulus T, Garris C, Van de Velde N, Chounta V, Deger K. 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 View
  43. 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 View
  44. Paul M, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1 View
  45. Kim S, Hawkins K. The psychology of social media communication in influencing prevention intentions during the 2019 U.S. measles outbreak. Computers in Human Behavior 2020;111:106428 View
  46. 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 View
  47. Kunneman F, Lambooij M, Wong A, Bosch A, Mollema L. Monitoring stance towards vaccination in twitter messages. BMC Medical Informatics and Decision Making 2020;20(1) View
  48. Bonnevie E, Goldbarg J, Gallegos-Jeffrey A, Rosenberg S, Wartella E, Smyser J. Content Themes and Influential Voices Within Vaccine Opposition on Twitter, 2019. American Journal of Public Health 2020;110(S3):S326 View
  49. Wicke P, Bolognesi M, Athanasopoulos P. Framing COVID-19: How we conceptualize and discuss the pandemic on Twitter. PLOS ONE 2020;15(9):e0240010 View
  50. Postma L, 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 View
  51. Gencoglu O, Gruber M. Causal Modeling of Twitter Activity during COVID-19. Computation 2020;8(4):85 View
  52. Gencoglu O. Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19. Machine Learning and Knowledge Extraction 2020;2(4):603 View
  53. 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 View
  54. Al-Khalifa K, AlSheikh R, Alsahafi Y, Alkhalifa A, Sadaf S, Muazen Y, Al-Moumen S, Yermal A. Dental care during the COVID-19 Pandemic: An Arabic tweets analysis (Preprint). JMIR Public Health and Surveillance 2020 View
  55. Momynaliev K, Khoperskay L, Pshenichnaya N, Abuova G, Akimkin V. Infodemiological study of coronavirus epidemic using Google Trends in Central Asian Republics of Kazakhstan, Kyrgyzstan, Uzbekistan, Tajikistan. Medical alphabet 2021;(34):47 View
  56. Karafillakis E, Martin S, Simas C, Olsson K, Takacs J, Dada S, Larson H. Methods for Social Media Monitoring Related to Vaccination: Systematic Scoping Review. JMIR Public Health and Surveillance 2021;7(2):e17149 View
  57. 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 View
  58. Alvarez-Galvez J, Suarez-Lledo V, Rojas-Garcia A. Determinants of Infodemics During Disease Outbreaks: A Systematic Review. Frontiers in Public Health 2021;9 View
  59. Wicke P, Bolognesi M. Covid-19 Discourse on Twitter: How the Topics, Sentiments, Subjectivity, and Figurative Frames Changed Over Time. Frontiers in Communication 2021;6 View
  60. Nguyen T, Le X. How social media fosters the elders' COVID-19 preventive behaviors: perspectives of information value and perceived threat. Library Hi Tech 2021;39(3):776 View
  61. Xie R, Chu S, Chiu D, 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 View
  62. 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 View
  63. Bonnevie E, Sittig J, Smyser J. The case for tracking misinformation the way we track disease. Big Data & Society 2021;8(1):205395172110138 View
  64. Bonnevie E, Goldbarg J, Gallegos-Jeffry A, Rosenberg S, 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 View
  65. Al-Khalifa K, AlSheikh R, Alsahafi Y, Alkhalifa A, Sadaf S, Al-Moumen S, Muazen Y, Shetty A. Dental Care in the Arab Countries During the COVID-19 Pandemic: An Infodemiological Study. Risk Management and Healthcare Policy 2021;Volume 14:2153 View
  66. 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 View
  67. 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 View
  68. Ingrams A. 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 View
  69. Ansah P. 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 View
  70. 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 View
  71. Izhar T, Torabi T. Online searching trend on Covid-19 using Google trend: infodemiological study in Malaysia. International Journal of Information Technology 2022;14(2):675 View
  72. 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 View
  73. Stege H, Schneider S, Forschner A, Eigentler T, Nashan D, Huening S, Meiss F, Lehr S, Kaatz M, Kuchen R, Kaehler K, 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 View
  74. 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 View
  75. 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 View
  76. Mitchell S. 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 View
  77. Dong X, Lian Y. A review of social media-based public opinion analyses: Challenges and recommendations. Technology in Society 2021;67:101724 View
  78. 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 View
  79. 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 View
  80. 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 View
  81. Momynaliev K, Khoroshun D, Akimkin V. Online queries as a criterion for evaluating epidemiological status and effectiveness of COVID-19 control measures in Russia: results from Yandex.Wordstat analysis. BMJ Open 2022;12(7):e056716 View
  82. Khoroshun D, Momynaliev K, Voronin E, Akimkin V. Analysis of Yandex search queries related to COVID‑19 in Russian Federation. Medical alphabet 2022;(14):14 View
  83. 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 View
  84. Kakizawa H. The value of public service broadcasting in Japan during COVID-19 pandemic: An analysis of WTP by Blinder-Oaxaca decomposition. Telecommunications Policy 2023;47(3):102523 View
  85. Arendt F, Scherr S. News-stimulated public-attention dynamics and vaccination coverage during a measles outbreak: An observational study. Social Science & Medicine 2020;265:113495 View
  86. Friemel T, Geber S. Social Distancing during the COVID-19 Pandemic in Switzerland: Health Protective Behavior in the Context of Communication and Perceptions of Efficacy, Norms, and Threat. Health Communication 2023;38(4):779 View
  87. YAMASHITA R. A Trend Analysis of Emotions on the Issue of Unidentified Land Owners in Social Media:Case Study of Land Acquisition of Water Resource Area by Foreign Investors. Studies in Regional Science 2021;51(1):115 View
  88. Khademi Habibabadi S, Delir Haghighi P, Burstein F, Buttery J. Vaccine Adverse Event Mining of Twitter Conversations: 2-Phase Classification Study. JMIR Medical Informatics 2022;10(6):e34305 View
  89. Jiang Q, Xue Y, Hu Y, Li Y. Public Social Media Discussions on Agricultural Product Safety Incidents: Chinese African Swine Fever Debate on Weibo. Frontiers in Psychology 2022;13 View
  90. Pilipiec P, Samsten I, Bota A, Rocha L. Surveillance of communicable diseases using social media: A systematic review. PLOS ONE 2023;18(2):e0282101 View
  91. Déguilhem A, Malaab J, Talmatkadi M, Renner S, Foulquié P, Fagherazzi G, Loussikian P, Marty T, Mebarki A, Texier N, Schuck S. Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media. JMIR Infodemiology 2022;2(2):e39849 View
  92. Shi C, So M, Stelmach S, Earn A, Earn D, Dushoff J. From science to politics: COVID-19 information fatigue on YouTube. BMC Public Health 2022;22(1) View
  93. Sano Y, Hori A, Kolahi J. 12-year observation of tweets about rubella in Japan: A retrospective infodemiology study. PLOS ONE 2023;18(5):e0285101 View
  94. Mitchell S, Beanlands J. “The mask is not for you” : A framing analysis of pro- and anti-mask sentiment on Twitter. Health & New Media Research 2022;6(1):3 View
  95. Grage L, Cuellar M. Did text-based news-media coverage about the COVID-19 pandemic increase vaccine uptake? A population-based study in Alaska. International Journal of Circumpolar Health 2023;82(1) View
  96. Qiu D, Huang L. Comparative analysis of epidemic public opinion and policies in two regions of China based on big data. Intelligent Data Analysis 2024;28(2):533 View
  97. Diaz M, Medford R, Lehmann C, Petersen C. The lived experience of people with disabilities during the COVID-19 pandemic on Twitter: Content analysis. DIGITAL HEALTH 2023;9 View
  98. Su M, Cheng D, Xu Y, Weng F. An improved BERT method for the evolution of network public opinion of major infectious diseases: Case Study of COVID-19. Expert Systems with Applications 2023;233:120938 View
  99. Fu J, Li C, Zhou C, Li W, Lai J, Deng S, Zhang Y, Guo Z, Wu Y. Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review. Journal of Medical Internet Research 2023;25:e43349 View
  100. Yuda Kusuma I, Pratiwi H, Fitri Khairunnisa S, Ayu Eka Pitaloka D, Arizandi Kurnianto A. The assessment of Twitter discourse on the new COVID-19 variant, XBB.1.5, through social network analysis. Vaccine: X 2023;14:100322 View
  101. Ribeiro F, Silva S, Perona J. Estudar o desconhecido, publicar o possível? A resposta à pandemia da covid-19 nas principais revistas Scopus em Ciências da Comunicação. Palabra Clave 2024;26(4):1 View
  102. Pratiwi H, Benkő R, Kusuma I. Navigating the asthma network on Twitter: Insights from social network and sentiment analysis. DIGITAL HEALTH 2024;10 View
  103. Zhang Y, Fu J, Lai J, Deng S, Guo Z, Zhong C, Tang J, Cao W, Wu Y. Reporting of Ethical Considerations in Qualitative Research Utilizing Social Media Data on Public Health Care: Scoping Review. Journal of Medical Internet Research 2024;26:e51496 View

Books/Policy Documents

  1. Shin E, Shaban-Nejad A. Public Health Intelligence and the Internet. View
  2. Rustagi S, Patel D. Transactions on Large-Scale Data- and Knowledge-Centered Systems XLIII. View
  3. Lee B, Jeong H, Shin E. Explainable AI in Healthcare and Medicine. View
  4. Novak J, Maljur T, Drenska K. HCI International 2022 – Late Breaking Papers: Interacting with eXtended Reality and Artificial Intelligence. View
  5. Shaikh S, Yayilgan S, Zoto E, Abomhara M. Intelligent Computing. View
  6. Melton C, Bae J, Olusanya O, Brenas J, Shin E, Shaban-Nejad A. Multimodal AI in Healthcare. View