This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2452) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Mass Media/Social Media Communication and Campaigns (461) Outbreak and Pandemic Preparedness and Management (1727) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19611, first published .
Assessment of the Impact of Media Coverage on COVID-19–Related Google Trends Data: Infodemiology Study

Assessment of the Impact of Media Coverage on COVID-19–Related Google Trends Data: Infodemiology Study

Assessment of the Impact of Media Coverage on COVID-19–Related Google Trends Data: Infodemiology Study

Authors of this article:

Bernardo Sousa-Pinto1, 2 Author Orcid Image ;   Aram Anto3 Author Orcid Image ;   Wienia Czarlewski3, 4 Author Orcid Image ;   Josep M Anto5, 6, 7 Author Orcid Image ;   João Almeida Fonseca1, 2 Author Orcid Image ;   Jean Bousquet8, 9, 10 Author Orcid Image
Article Authors Cited by (75) Tweetations (11) Metrics

Journals

  1. Sousa-Pinto B, Heffler E, Antó A, Czarlewski W, Bedbrook A, Gemicioglu B, Canonica G, Antó J, Fonseca J, Bousquet J. Anomalous asthma and chronic obstructive pulmonary disease Google Trends patterns during the COVID-19 pandemic. Clinical and Translational Allergy 2020;10(1) View
  2. Lampos V, Majumder M, Yom-Tov E, Edelstein M, Moura S, Hamada Y, Rangaka M, McKendry R, Cox I. Tracking COVID-19 using online search. npj Digital Medicine 2021;4(1) View
  3. Asadzadeh A, Pakkhoo S, Saeidabad M, Khezri H, Ferdousi R. Information technology in emergency management of COVID-19 outbreak. Informatics in Medicine Unlocked 2020;21:100475 View
  4. Roncon L, Zuin M, Barco S, Zuliani G, Konstantinides S. Increased interest in acute pulmonary embolism in Italy during the COVID-19 pandemic: a google trends-based analysis. Journal of Thrombosis and Thrombolysis 2021;52(1):92 View
  5. Johnson A, Bhaumik R, Tabidze I, Mehta S. Nowcasting Sexually Transmitted Infections in Chicago: Predictive Modeling and Evaluation Study Using Google Trends. JMIR Public Health and Surveillance 2020;6(4):e20588 View
  6. Chrzanowski J, Sołek J, Fendler W, Jemielniak D. Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak: Search Trends Analysis. Journal of Medical Internet Research 2021;23(4):e26331 View
  7. Huynh Dagher S, Lamé G, Hubiche T, Ezzedine K, Duong T. The Influence of Media Coverage and Governmental Policies on Google Queries Related to COVID-19 Cutaneous Symptoms: Infodemiology Study. JMIR Public Health and Surveillance 2021;7(2):e25651 View
  8. Sandhu A, Hany R, Hirohata A, Hishita S, Kimlicka K, Naito M, Nishimura C. Global snapshot of the effects of the COVID-19 pandemic on the research activities of materials scientists between Spring and Autumn 2020. Science and Technology of Advanced Materials 2021;22(1):173 View
  9. Pilz A, Tizek L, Rüth M, Seiringer P, Biedermann T, Zink A. Interest in Sexually Transmitted Infections: Analysis of Web Search Data Terms in Eleven Large German Cities from 2015 to 2019. International Journal of Environmental Research and Public Health 2021;18(5):2771 View
  10. ESEN M. COVID-19 salgınıyla ilişkili semptomların Türkiye’den gerçekleştirilen internet arama motoru sorgularının incelenmesi. Journal of Medicine and Palliative Care 2021;2(1):7 View
  11. Al-Laith A, Alenezi M. Monitoring People’s Emotions and Symptoms from Arabic Tweets during the COVID-19 Pandemic. Information 2021;12(2):86 View
  12. El-Toukhy S. Insights From the SmokeFree.gov Initiative Regarding the Use of Smoking Cessation Digital Platforms During the COVID-19 Pandemic: Cross-sectional Trends Analysis Study. Journal of Medical Internet Research 2021;23(3):e24593 View
  13. 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
  14. Mangono T, Smittenaar P, Caplan Y, Huang V, Sutermaster S, Kemp H, Sgaier S. Information-Seeking Patterns During the COVID-19 Pandemic Across the United States: Longitudinal Analysis of Google Trends Data. Journal of Medical Internet Research 2021;23(5):e22933 View
  15. Fang J, Zhang X, Tong Y, Xia Y, Liu H, Wu K. Baidu Index and COVID-19 Epidemic Forecast: Evidence From China. Frontiers in Public Health 2021;9 View
  16. Meng J, Su Q, Zhang J, Wang L, Xu R, Yan C. Epidemics, Public Sentiment, and Infectious Disease Equity Market Volatility. Frontiers in Public Health 2021;9 View
  17. Rovetta A. Reliability of Google Trends: Analysis of the Limits and Potential of Web Infoveillance During COVID-19 Pandemic and for Future Research. Frontiers in Research Metrics and Analytics 2021;6 View
  18. Rotter D, Doebler P, Schmitz F. Interests, Motives, and Psychological Burdens in Times of Crisis and Lockdown: Google Trends Analysis to Inform Policy Makers. Journal of Medical Internet Research 2021;23(6):e26385 View
  19. Pascual-Ferrá P, Alperstein N, Barnett D, Rimal R. Toxicity and verbal aggression on social media: Polarized discourse on wearing face masks during the COVID-19 pandemic. Big Data & Society 2021;8(1) View
  20. Paramita M, Orphanou K, Christoforou E, Otterbacher J, Hopfgartner F. Do you see what I see? Images of the COVID-19 pandemic through the lens of Google. Information Processing & Management 2021;58(5):102654 View
  21. Wei S, Ma M, Wen X, Wu C, Zhu G, Zhou X. Online Public Attention Toward Premature Ejaculation in Mainland China: Infodemiology Study Using the Baidu Index. Journal of Medical Internet Research 2021;23(8):e30271 View
  22. Sousa-Pinto B, Halonen J, Antó A, Jormanainen V, Czarlewski W, Bedbrook A, Papadopoulos N, Freitas A, Haahtela T, Antó J, Fonseca J, Bousquet J. Prediction of Asthma Hospitalizations for the Common Cold Using Google Trends: Infodemiology Study. Journal of Medical Internet Research 2021;23(7):e27044 View
  23. SeyyedHosseini S, BasirianJahromi R. COVID-19 pandemic in the Middle East countries: coronavirus-seeking behavior versus coronavirus-related publications. Scientometrics 2021;126(9):7503 View
  24. Husnayain A, Chuang T, Fuad A, Su E. High variability in model performance of Google relative search volumes in spatially clustered COVID-19 areas of the USA. International Journal of Infectious Diseases 2021;109:269 View
  25. Sato K, Mano T, Iwata A, Toda T. Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity. BMC Medical Research Methodology 2021;21(1) View
  26. Rovetta A. The Impact of COVID-19 on Conspiracy Hypotheses and Risk Perception in Italy: Infodemiological Survey Study Using Google Trends. JMIR Infodemiology 2021;1(1):e29929 View
  27. Pian W, Chi J, Ma F. The causes, impacts and countermeasures of COVID-19 “Infodemic”: A systematic review using narrative synthesis. Information Processing & Management 2021;58(6):102713 View
  28. Tozzi A, Gesualdo F, Urbani E, Sbenaglia A, Ascione R, Procopio N, Croci I, Rizzo C. Digital Surveillance Through an Online Decision Support Tool for COVID-19 Over One Year of the Pandemic in Italy: Observational Study. Journal of Medical Internet Research 2021;23(8):e29556 View
  29. Chejfec-Ciociano J, Martínez-Herrera J, Parra-Guerra A, Chejfec R, Barbosa-Camacho F, Ibarrola-Peña J, Cervantes-Guevara G, Cervantes-Cardona G, Fuentes-Orozco C, Cervantes-Pérez E, García-Reyna B, González-Ojeda A. Misinformation About and Interest in Chlorine Dioxide During the COVID-19 Pandemic in Mexico Identified Using Google Trends Data: Infodemiology Study. JMIR Infodemiology 2022;2(1):e29894 View
  30. Simonart T, Lam Hoai X, de Maertelaer V. Worldwide Evolution of Vaccinable and Nonvaccinable Viral Skin Infections: Google Trends Analysis. JMIR Dermatology 2022;5(4):e35034 View
  31. Deiner M, Kaur G, McLeod S, Schallhorn J, Chodosh J, Hwang D, Lietman T, Porco T. A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study. Journal of Medical Internet Research 2022;24(7):e27310 View
  32. Ming W, Huang F, Chen Q, Liang B, Jiao A, Liu T, Wu H, Akinwunmi B, Li J, Liu G, Zhang C, Huang J, Liu Q. Understanding Health Communication Through Google Trends and News Coverage for COVID-19: Multinational Study in Eight Countries. JMIR Public Health and Surveillance 2021;7(12):e26644 View
  33. Hafenscher P, Jankó F. Flames and Viruses: Australian and Hungarian Media Representation of the Australian Bushfires and the COVID-19 Pandemic, A Case Study. Climate 2022;10(11):163 View
  34. Cai O, Sousa-Pinto B. United States Influenza Search Patterns Since the Emergence of COVID-19: Infodemiology Study. JMIR Public Health and Surveillance 2022;8(3):e32364 View
  35. Simonart T, Lam Hoai X, De Maertelaer V. Epidemiologic evolution of common cutaneous infestations and arthropod bites: A Google Trends analysis. JAAD International 2021;5:69 View
  36. Khosrowjerdi M, Fylking C, Zeraatkar N. Online information seeking during the COVID-19 pandemic: A cross-country analysis. IFLA Journal 2023;49(2):328 View
  37. Satpathy P, Kumar S, Prasad P. Suitability of Google Trends™ for Digital Surveillance During Ongoing COVID-19 Epidemic: A Case Study from India. Disaster Medicine and Public Health Preparedness 2023;17 View
  38. Goupil de Bouillé J, Luong Nguyen L, Crépey P, Garlantezec R, Doré V, Dumas A, Ben Mechlia M, Tattevin P, Gaudart J, Spire B, Lert F, Yazdanpanah Y, Delaugerre C, Noret M, Zeggagh J. Transmission of SARS-CoV-2 during indoor clubbing events: A clustered randomized, controlled, multicentre trial protocol. Frontiers in Public Health 2022;10 View
  39. Loiacono L, Puglisi R, Rizzo L, Secomandi R. Pandemic knowledge and regulation effectiveness: Evidence from COVID-19. Journal of Comparative Economics 2022;50(3):768 View
  40. Samadbeik M, Garavand A, Aslani N, Ebrahimzadeh F, Fatehi F, Kardeş S. Assessing the online search behavior for COVID-19 outbreak: Evidence from Iran. PLOS ONE 2022;17(7):e0267818 View
  41. Vieira R, Sousa-Pinto B, Anto J, Sheikh A, Klimek L, Zuberbier T, Fonseca J, Bousquet J. Usage patterns of oral H1-antihistamines in 10 European countries: A study using MASK-air® and Google Trends real-world data. World Allergy Organization Journal 2022;15(7):100660 View
  42. Chen J, Mi H, Fu J, Zheng H, Zhao H, Yuan R, Guo H, Zhu K, Zhang Y, Lyu H, Zhang Y, She N, Ren X. Construction and validation of a COVID-19 pandemic trend forecast model based on Google Trends data for smell and taste loss. Frontiers in Public Health 2022;10 View
  43. Kłak A, Furmańczyk K, Nowicka P, Mańczak M, Barańska A, Religioni U, Siekierska A, Ambroziak M, Chłopek M. The Relationship between Searches for COVID-19 Vaccines and Dynamics of Vaccinated People in Poland: An Infodemiological Study. International Journal of Environmental Research and Public Health 2022;19(20):13275 View
  44. Saegner T, Austys D. Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review. International Journal of Environmental Research and Public Health 2022;19(19):12394 View
  45. Wang B, Liang B, Chen Q, Wang S, Wang S, Huang Z, Long Y, Wu Q, Xu S, Jinna P, Yang F, Ming W, Liu Q. COVID-19 Related Early Google Search Behavior and Health Communication in the United States: Panel Data Analysis on Health Measures. International Journal of Environmental Research and Public Health 2023;20(4):3007 View
  46. Trevino J, Malik S, Schmidt M. Integrating Google Trends Search Engine Query Data Into Adult Emergency Department Volume Forecasting: Infodemiology Study. JMIR Infodemiology 2022;2(1):e32386 View
  47. Lorenzoni V, Andreozzi G, Bazzani A, Casigliani V, Pirri S, Tavoschi L, Turchetti G. How Italy Tweeted about COVID-19: Detecting Reactions to the Pandemic from Social Media. International Journal of Environmental Research and Public Health 2022;19(13):7785 View
  48. Elyashar A, Plochotnikov I, Cohen I, Puzis R, Cohen O. The State of Mind of Health Care Professionals in Light of the COVID-19 Pandemic: Text Analysis Study of Twitter Discourses. Journal of Medical Internet Research 2021;23(10):e30217 View
  49. Ma M, Ye S. The COVID-19 pandemic and seeking information about condoms online: an infodemiology approach. Psychology & Health 2023;38(9):1128 View
  50. Nowak B, Kamiński M, Owczarek B, Szulińska M, Bogdański P. Availability of Cardiodiabetological Drugs in Poland during the First Year of COVID-19 Pandemic: Retrospective Study. BioMed 2022;2(1):117 View
  51. Ito T. Global monitoring of public interest in preventive measures against COVID-19 via analysis of Google Trends: an infodemiology and infoveillance study. BMJ Open 2022;12(8):e060715 View
  52. Leung C, Li K, Wei V, Tang A, Wong S, Lee S, Kwok K. Profiling vaccine believers and skeptics in nurses: A latent profile analysis. International Journal of Nursing Studies 2022;126:104142 View
  53. Ilias I, Milionis C, Koukkou E. COVID-19 and thyroid disease: An infodemiological pilot study. World Journal of Methodology 2022;12(3):99 View
  54. An L, Russell D, Mihalcea R, Bacon E, Huffman S, Resnicow K. Online Search Behavior Related to COVID-19 Vaccines: Infodemiology Study. JMIR Infodemiology 2021;1(1):e32127 View
  55. Ma M. Heightened religiosity proactively and reactively responds to the COVID-19 pandemic across the globe: Novel insights from the parasite-stress theory of sociality and the behavioral immune system theory. International Journal of Intercultural Relations 2022;90:38 View
  56. Yang M, Lim M, Qu Y, Li X, Ni D. Deep neural networks with L1 and L2 regularization for high dimensional corporate credit risk prediction. Expert Systems with Applications 2023;213:118873 View
  57. Springer S, Strzelecki A, Zieger M. Maximum generable interest: A universal standard for Google Trends search queries. Healthcare Analytics 2023;3:100158 View
  58. Jormand H, Barati M, Bashirian S, Khazaei S, Jenabi E, Zareian S. Developing and validation of COVID-19 media literacy scale among students during the COVID-19 pandemic. BMC Psychology 2023;11(1) View
  59. Yeung A, Parvanov E, Horbańczuk J, Kletecka-Pulker M, Kimberger O, Willschke H, Atanasov A. Public interest in different types of masks and its relationship with pandemic and policy measures during the COVID-19 pandemic: a study using Google Trends data. Frontiers in Public Health 2023;11 View
  60. Marín-González E, Navalhas I, Dijkstra A, De Jong A, Luís C. Science journalism in pandemic times: perspectives on the science-media relationship from COVID-19 researchers in Southern Europe. Frontiers in Communication 2023;8 View
  61. Miconi A, Pezzano S, Risi E. Framing pandemic news. Empirical research on Covid-19 representation in the Italian TV news. Iluminace 2023;35(1):65 View
  62. Morokhovets H, Lysanets Y, Kaidashev I. INFODEMIOLOGY: USING GOOGLE TRENDS AS A RESEARCH TOOL DURING THE COVID-19 PANDEMIC. The Medical and Ecological Problems 2023;27(3-4):3 View
  63. Marshall D, McRee A, Gower A, Reiter P. Views about vaccines and how views changed during the COVID-19 pandemic among a national sample of young gay, bisexual, and other men who have sex with men. Human Vaccines & Immunotherapeutics 2023;19(3) View
  64. Sidorenkov G, Vonk J, Grzegorczyk M, Cortés-Ibañez F, de Bock G, Lounis M. Factors associated with SARS-COV-2 positive test in Lifelines. PLOS ONE 2023;18(11):e0294556 View
  65. Mancini A, Sowards S, Blumberg A, Lynch R, Fardella G, Maewsky N, Prati G. Media exposure related to COVID-19 is associated with worse mental health consequences in the United States compared to Italy. Anxiety, Stress, & Coping 2024;37(3):348 View
  66. Lauriola M, Di Cicco G, Savadori L. Apocalypse now or later? Nuclear war risk perceptions mirroring media coverage and emotional tone shifts in Italian news. Judgment and Decision Making 2024;19 View
  67. Zahradníčková K, Kašparová I. Gift, purchase or mask diplomacy? Hesitant reception of China’s face masks during the first COVID-19 wave in Czech public discourse. Journal of Contemporary Central and Eastern Europe 2024;32(1):149 View
  68. Azmoude E, larki M, Marvi N, Roudsari R. Public Reproductive Health Concerns Related to the COVID-19 Vaccination: A Retrospective Analysis of Google Trends Data in Iran. Current Womens Health Reviews 2024;20(3) View
  69. Şen Yavuz B, Güneyligil Kazaz T, Akbeyaz Şivet E, Kargul B. Prediction of the Spread of the COVID-19 Pandemic with Google Searches: An Infodemiological Approach. ADO Klinik Bilimler Dergisi 2024;13(2):358 View
  70. Rovetta A. Google trends in infodemiology: Methodological steps to avoid irreproducible results and invalid conclusions. International Journal of Medical Informatics 2024;190:105563 View
  71. Sousa-Pinto B, Vieira R, Marques-Cruz M, Bognanni A, Gil-Mata S, Jankin S, Amaro J, Pinheiro L, Mota M, Giovannini M, de las Vecillas L, Pereira A, Lityńska J, Samolinski B, Bernstein J, Dykewicz M, Hofmann-Apitius M, Jacobs M, Papadopoulos N, Williams S, Zuberbier T, Fonseca J, Cruz-Correia R, Bousquet J, Schünemann H. Artificial Intelligence–Supported Development of Health Guideline Questions. Annals of Internal Medicine 2024;177(11):1518 View

Books/Policy Documents

  1. Konac A, Barut Y. Handbook of Research on Representing Health and Medicine in Modern Media. View
  2. Pérez-Díaz P, Albert-Botella L. Communication and Smart Technologies. View
  3. Lefèvre T, Colineaux H, Morgand C, Tournois L, Delpierre C. Artificial Intelligence in Covid-19. View