Published on in Vol 22, No 4 (2020): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19016, first published .
Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study

Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study

Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study

Journals

  1. Rovetta A, Bhagavathula A. Global Infodemiology of COVID-19: Analysis of Google Web Searches and Instagram Hashtags. Journal of Medical Internet Research 2020;22(8):e20673 View
  2. Domínguez-Salas S, Gómez-Salgado J, Andrés-Villas M, Díaz-Milanés D, Romero-Martín M, Ruiz-Frutos C. Psycho-Emotional Approach to the Psychological Distress Related to the COVID-19 Pandemic in Spain: A Cross-Sectional Observational Study. Healthcare 2020;8(3):190 View
  3. Badell-Grau R, Cuff J, Kelly B, Waller-Evans H, Lloyd-Evans E. Investigating the Prevalence of Reactive Online Searching in the COVID-19 Pandemic: Infoveillance Study. Journal of Medical Internet Research 2020;22(10):e19791 View
  4. Alvarez-Risco A, Mejia C, Delgado-Zegarra J, Del-Aguila-Arcentales S, Arce-Esquivel A, Valladares-Garrido M, Rosas del Portal M, Villegas L, Curioso W, Sekar M, Yáñez J. The Peru Approach against the COVID-19 Infodemic: Insights and Strategies. The American Journal of Tropical Medicine and Hygiene 2020;103(2):583 View
  5. OLIVEIRA L, ZANATTA F. Self-reported dental treatment needs during the COVID-19 outbreak in Brazil: an infodemiological study. Brazilian Oral Research 2020;34 View
  6. Qazi U, Imran M, Ofli F. GeoCoV19. SIGSPATIAL Special 2020;12(1):6 View
  7. Doogan C, Buntine W, Linger H, Brunt S. Public Perceptions and Attitudes Toward COVID-19 Nonpharmaceutical Interventions Across Six Countries: A Topic Modeling Analysis of Twitter Data. Journal of Medical Internet Research 2020;22(9):e21419 View
  8. Hecht N, Wessels L, Werft F, Schneider U, Czabanka M, Vajkoczy P. Need for ensuring care for neuro-emergencies—lessons learned from the COVID-19 pandemic. Acta Neurochirurgica 2020;162(8):1795 View
  9. De Santis E, Martino A, Rizzi A. An Infoveillance System for Detecting and Tracking Relevant Topics From Italian Tweets During the COVID-19 Event. IEEE Access 2020;8:132527 View
  10. Warin T. Global Research on Coronaviruses: An R Package. Journal of Medical Internet Research 2020;22(8):e19615 View
  11. Laato S, Islam A, Farooq A, Dhir A. Unusual purchasing behavior during the early stages of the COVID-19 pandemic: The stimulus-organism-response approach. Journal of Retailing and Consumer Services 2020;57:102224 View
  12. de Melo T, Figueiredo C. A first public dataset from Brazilian twitter and news on COVID-19 in Portuguese. Data in Brief 2020;32:106179 View
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  14. Ming L, Untong N, Aliudin N, Osili N, Kifli N, Tan C, Goh K, Ng P, Al-Worafi Y, Lee K, Goh H. Mobile Health Apps on COVID-19 Launched in the Early Days of the Pandemic: Content Analysis and Review. JMIR mHealth and uHealth 2020;8(9):e19796 View
  15. Larrouquere L, Gabin M, Poingt E, Mouffak A, Hlavaty A, Lepelley M, Khouri C, Bellier A, Alexandre J, Bedouch P, Bertoletti L, Bordet R, Bouhanick B, Jonville‐Bera A, Laporte S, Le Jeunne C, Letinier L, Micallef J, Naudet F, Roustit M, Molimard M, Richard V, Cracowski J. Genesis of an emergency public drug information website by the French Society of Pharmacology and Therapeutics during the COVID‐19 pandemic. Fundamental & Clinical Pharmacology 2020;34(3):389 View
  16. 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
  17. Pobiruchin M, Zowalla R, Wiesner M. Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study. Journal of Medical Internet Research 2020;22(8):e19629 View
  18. Kaya T. The changes in the effects of social media use of Cypriots due to COVID-19 pandemic. Technology in Society 2020;63:101380 View
  19. Cignarelli A, Sansone A, Caruso I, Perrini S, Natalicchio A, Laviola L, Jannini E, Giorgino F. Diabetes in the Time of COVID-19: A Twitter-Based Sentiment Analysis. Journal of Diabetes Science and Technology 2020;14(6):1131 View
  20. Chen E, Lerman K, Ferrara E. Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set. JMIR Public Health and Surveillance 2020;6(2):e19273 View
  21. Mackey T, Purushothaman V, Li J, Shah N, Nali M, Bardier C, Liang B, Cai M, Cuomo R. Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study. JMIR Public Health and Surveillance 2020;6(2):e19509 View
  22. Kamiński M, Muth A, Bogdański P. Smoking, Vaping, and Tobacco Industry During COVID-19 Pandemic: Twitter Data Analysis. Cyberpsychology, Behavior, and Social Networking 2020;23(12):811 View
  23. Qazi U, Imran M, Ofli F. GeoCoV19. SIGSPATIAL Special 2020;12(1):6 View
  24. Fagherazzi G, Goetzinger C, Rashid M, Aguayo G, Huiart L. Digital Health Strategies to Fight COVID-19 Worldwide: Challenges, Recommendations, and a Call for Papers. Journal of Medical Internet Research 2020;22(6):e19284 View
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  26. Budhwani H, Sun R. Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the “Chinese virus” on Twitter: Quantitative Analysis of Social Media Data. Journal of Medical Internet Research 2020;22(5):e19301 View
  27. Campos-Castillo C, Laestadius L. Racial and Ethnic Digital Divides in Posting COVID-19 Content on Social Media Among US Adults: Secondary Survey Analysis. Journal of Medical Internet Research 2020;22(7):e20472 View
  28. Zhu B, Zheng X, Liu H, Li J, Wang P. Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics. Chaos, Solitons & Fractals 2020;140:110123 View
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  34. Vlasschaert C, Topf J, Hiremath S. Proliferation of Papers and Preprints During the Coronavirus Disease 2019 Pandemic: Progress or Problems With Peer Review?. Advances in Chronic Kidney Disease 2020;27(5):418 View
  35. Kamiński M, Szymańska C, Nowak J. Whose Tweets on COVID-19 Gain the Most Attention: Celebrities, Political, or Scientific Authorities?. Cyberpsychology, Behavior, and Social Networking 2021;24(2):123 View
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  37. Chang C, Monselise M, Yang C. What Are People Concerned About During the Pandemic? Detecting Evolving Topics about COVID-19 from Twitter. Journal of Healthcare Informatics Research 2021;5(1):70 View
  38. Massey D, Huang C, Lu Y, Cohen A, Oren Y, Moed T, Matzner P, Mahajan S, Caraballo C, Kumar N, Xue Y, Ding Q, Dreyer R, Roy B, Krumholz H. Engagement With COVID-19 Public Health Measures in the United States: A Cross-sectional Social Media Analysis from June to November 2020. Journal of Medical Internet Research 2021;23(6):e26655 View
  39. Grabowski D, Overgaard M, Meldgaard J, Johansen L, Willaing I. Disrupted Self-Management and Adaption to New Diabetes Routines: A Qualitative Study of How People with Diabetes Managed Their Illness during the COVID-19 Lockdown. Diabetology 2021;2(1):1 View
  40. Zhou X, Song Y, Jiang H, Wang Q, Qu Z, Zhou X, Jit M, Hou Z, Lin L. Comparison of Public Responses to Containment Measures During the Initial Outbreak and Resurgence of COVID-19 in China: Infodemiology Study. Journal of Medical Internet Research 2021;23(4):e26518 View
  41. Shen T, Chen A, Bovonratwet P, Shen C, Su E. COVID-19–Related Internet Search Patterns Among People in the United States: Exploratory Analysis. Journal of Medical Internet Research 2020;22(11):e22407 View
  42. Salvi C, Iannello P, Cancer A, McClay M, Rago S, Dunsmoor J, Antonietti A. Going Viral: How Fear, Socio-Cognitive Polarization and Problem-Solving Influence Fake News Detection and Proliferation During COVID-19 Pandemic. Frontiers in Communication 2021;5 View
  43. Nsoesie E, Cesare N, Müller M, Ozonoff A. COVID-19 Misinformation Spread in Eight Countries: Exponential Growth Modeling Study. Journal of Medical Internet Research 2020;22(12):e24425 View
  44. Basch C, Fera J, Pierce I, Basch C. Promoting Mask Use on TikTok: Descriptive, Cross-sectional Study. JMIR Public Health and Surveillance 2021;7(2):e26392 View
  45. Farsi D. Social Media and Health Care, Part I: Literature Review of Social Media Use by Health Care Providers. Journal of Medical Internet Research 2021;23(4):e23205 View
  46. Singh T, Roberts K, Cohen T, Cobb N, Wang J, Fujimoto K, Myneni S. Social Media as a Research Tool (SMaaRT) for Risky Behavior Analytics: Methodological Review. JMIR Public Health and Surveillance 2020;6(4):e21660 View
  47. Carnot M, Bernardino J, Laranjeiro N, Gonçalo Oliveira H. Applying Text Analytics for Studying Research Trends in Dependability. Entropy 2020;22(11):1303 View
  48. Gencoglu O, Gruber M. Causal Modeling of Twitter Activity during COVID-19. Computation 2020;8(4):85 View
  49. Chandrasekaran R, Mehta V, Valkunde T, Moustakas E. Topics, Trends, and Sentiments of Tweets About the COVID-19 Pandemic: Temporal Infoveillance Study. Journal of Medical Internet Research 2020;22(10):e22624 View
  50. Chintalapudi N, Battineni G, Amenta F. Sentimental Analysis of COVID-19 Tweets Using Deep Learning Models. Infectious Disease Reports 2021;13(2):329 View
  51. Petersen K, Gerken J. #Covid-19: An exploratory investigation of hashtag usage on Twitter. Health Policy 2021;125(4):541 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. Reuter K, Deodhar A, Makri S, Zimmer M, Berenbaum F, Nikiphorou E. The impact of the COVID-19 pandemic on people with rheumatic and musculoskeletal diseases: insights from patient-generated data on social media. Rheumatology 2021;60(SI):SI77 View
  54. Shah A, Yan X, Qayyum A, Naqvi R, Shah S. Mining topic and sentiment dynamics in physician rating websites during the early wave of the COVID-19 pandemic: Machine learning approach. International Journal of Medical Informatics 2021;149:104434 View
  55. Rustam F, Khalid M, Aslam W, Rupapara V, Mehmood A, Choi G, Mumtaz W. A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis. PLOS ONE 2021;16(2):e0245909 View
  56. Yang M, Han C. Revealing industry challenge and business response to Covid-19: a text mining approach. International Journal of Contemporary Hospitality Management 2021;33(4):1230 View
  57. Tsao S, Chen H, Tisseverasinghe T, Yang Y, Li L, Butt Z. What social media told us in the time of COVID-19: a scoping review. The Lancet Digital Health 2021;3(3):e175 View
  58. Cauberghe V, Van Wesenbeeck I, De Jans S, Hudders L, Ponnet K. How Adolescents Use Social Media to Cope with Feelings of Loneliness and Anxiety During COVID-19 Lockdown. Cyberpsychology, Behavior, and Social Networking 2021;24(4):250 View
  59. Do B, Tran T, Phan D, Nguyen H, Nguyen T, Nguyen H, Ha T, Dao H, Trinh M, Do T, Nguyen H, Vo T, Nguyen N, Tran C, Tran K, Duong T, Pham H, Nguyen L, Nguyen K, Chang P, Duong T. Health Literacy, eHealth Literacy, Adherence to Infection Prevention and Control Procedures, Lifestyle Changes, and Suspected COVID-19 Symptoms Among Health Care Workers During Lockdown: Online Survey. Journal of Medical Internet Research 2020;22(11):e22894 View
  60. Sharma S, Sharma S. Analyzing the depression and suicidal tendencies of people affected by COVID-19’s lockdown using sentiment analysis on social networking websites. Journal of Statistics and Management Systems 2021;24(1):115 View
  61. Chen S, Zhou L, Song Y, Xu Q, Wang P, Wang K, Ge Y, Janies D. A Novel Machine Learning Framework for Comparison of Viral COVID-19–Related Sina Weibo and Twitter Posts: Workflow Development and Content Analysis. Journal of Medical Internet Research 2021;23(1):e24889 View
  62. Xue J, Chen J, Hu R, Chen C, Zheng C, Su Y, Zhu T. Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach. Journal of Medical Internet Research 2020;22(11):e20550 View
  63. . Genèse d’un site d’information sur le bon usage du médicament au cours de la pandémie. Actualités Pharmaceutiques 2020;59(599):34 View
  64. Alomari E, Katib I, Albeshri A, Mehmood R. COVID-19: Detecting Government Pandemic Measures and Public Concerns from Twitter Arabic Data Using Distributed Machine Learning. International Journal of Environmental Research and Public Health 2021;18(1):282 View
  65. Garcia K, Berton L. Topic detection and sentiment analysis in Twitter content related to COVID-19 from Brazil and the USA. Applied Soft Computing 2021;101:107057 View
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  67. Zhao Y, Xi H, Zhang C. Exploring Occupation Differences in Reactions to COVID-19 Pandemic on Twitter. Data and Information Management 2021;5(1):110 View
  68. Xue J, Chen J, Chen C, Hu R, Zhu T. The Hidden Pandemic of Family Violence During COVID-19: Unsupervised Learning of Tweets. Journal of Medical Internet Research 2020;22(11):e24361 View
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  71. Piccinelli S, Moro S, Rita P. Air-travelers' concerns emerging from online comments during the COVID-19 outbreak. Tourism Management 2021;85:104313 View
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  377. Jiang Y, Popov A, Li Z, Hodgson M, Huang B. A Sensor-Based Simulation Method for Spatiotemporal Event Detection. ISPRS International Journal of Geo-Information 2024;13(5):141 View
  378. Li Y, Zeng Z, Yu L. Withdrawn: The crisis communication of the COVID-19 pandemic in media discourse: Text mining for infectious disease frames and environmental pollution. AQUA — Water Infrastructure, Ecosystems and Society 2024 View
  379. Lau N, Zhao X, O'Daffer A, Weissman H, Barton K. Pediatric Cancer Communication on Twitter: Natural Language Processing and Qualitative Content Analysis. JMIR Cancer 2024;10:e52061 View
  380. Kalaite M. Analisis Media Monitoring terhadap Brand EIGER pada Peluncuran Lini Koleksi “Safar Series”. Jurnal Bisnis dan Komunikasi Digital 2024;1(3):12 View
  381. Jigani A, Delcea C, Florescu M, Cotfas L. Tracking Happiness in Times of COVID-19: A Bibliometric Exploration. Sustainability 2024;16(12):4918 View
  382. Rabadán-Martín I, Barcos-Redín L, Pereira-Delgado J, Aguado-Correa F, Padilla-Garrido N. Topic-based engagement analysis: Focusing on hotel industry Twitter accounts. Tourism Management 2025;106:104981 View
  383. Zhang Z, Cheng Z, Gu T, Zhang Y. Determinants of users' unverified information sharing on social media platforms: A herding behavior perspective. Acta Psychologica 2024;248:104345 View
  384. Afyouni I, Hashim I, Aghbari Z, Elsaka T, Almahmoud M, Abualigah L. Insights from the COVID-19 Pandemic: A Survey of Data Mining and Beyond. Applied Spatial Analysis and Policy 2024 View
  385. Xu T, Zhu D, Yu Z, Dang J, Schiöth H. Differentiating the relationships between traditional and new media use and sleep quality during the COVID-19 pandemic: roles of psychological distress and age. Frontiers in Psychology 2024;15 View
  386. Meacham M, Nobles A, Bone C, Gilbert M, Thrul J, Mitra S. The Reddit cannabis subjective highness rating scale: Applying computational social science to explore psychological and environmental correlates of naturalistic cannabis use. PLOS ONE 2024;19(6):e0300290 View

Books/Policy Documents

  1. Barua R, Datta S, Bardhan N. Handbook of Research on Representing Health and Medicine in Modern Media. View
  2. Shah C, Sebastian M. Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation. View
  3. Sabuncu I, Aydin M. Data Science Advancements in Pandemic and Outbreak Management. View
  4. Casillo M, Colace F, Conte D, De Santo M, Lombardi M, Mottola S, Santaniello D. Computational Data and Social Networks. View
  5. Diván M, Singh M. Intelligent Human Computer Interaction. View
  6. Chen Z, Li Z, Ji Y, Stacks D, Yook B. Communicating Science in Times of Crisis. View
  7. Saire J, Cruz J. Information Management and Big Data. View
  8. Lähdeaho O, Hilmola O. Human Centred Intelligent Systems. View
  9. Sabuncu I. Handbook of Research on the Impacts and Implications of COVID-19 on the Tourism Industry. View
  10. Chire Saire J, Pineda-Briseño A. Artificial Intelligence for COVID-19. View
  11. Chauhan B, Jaiswar A, Bedi A, Verma S, Shrivastaw V, Vedrtnam A. Artificial Intelligence for COVID-19. View
  12. Abd-Alrazaq A, Schneider J, Alhuwail D, Hamdi M, Al-Kuwari S, Al-Thani D, Househ M. Multiple Perspectives on Artificial Intelligence in Healthcare. View
  13. Mehanović D, Mašetić Z, Vatreš A. Advanced Technologies, Systems, and Applications VI. View
  14. Hasti I, Nurmandi A, Muallidin I, Kurniawan D, Salahudin . Human Interaction, Emerging Technologies and Future Systems V. View
  15. Krishnan B, Kokatnoor S, Reddy V, Prathap B. Handbook of Research on the Global View of Open Access and Scholarly Communications. View
  16. Dhingra S, Arora R, Katariya P, Kumar A, Gupta V, Jain N. Sustainability Measures for COVID-19 Pandemic. View
  17. Kakulapati V, Reddy S, Kumar N. Lessons from COVID-19. View
  18. Rima B, Abderraouf B, Farid N. International Conference on Managing Business Through Web Analytics. View
  19. Löffelholz M. Risiken, Krisen, Konflikte. View
  20. Kumar A, Yun K, Negusse D, Misgna H, Ahmed M. Advances in Intelligent Computing and Communication. View
  21. Fernandez G, Maione C, Zaballa K, Bonnici N, Spitzberg B, Carter J, Yang H, McKew J, Bonora F, Ghodke S, Jin C, De Ocampo R, Kepner W, Tsou M. Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics. View
  22. Zhao Q, Nie L, Xu X. Comparative Studies on Pandemic Control Policies and the Resilience of Society. View
  23. Bhanye J, Bhanye A. The Palgrave Handbook of Global Social Problems. View
  24. Butt Z. Accelerating Strategic Changes for Digital Transformation in the Healthcare Industry. View
  25. Pousset R. Senizid. View
  26. Comito C. Artificial Intelligence in Healthcare and COVID-19. View
  27. Yıldırım E, Yazgan H, Özbek O, Günay A, Kocaçınar B, Şengel Ö, Akbulut F. Artificial Intelligence Applications and Innovations. View
  28. Comito C. Big Data – BigData 2023. View
  29. Wang G, Li W, Wu S, Bai Q, Lai E. PRICAI 2023: Trends in Artificial Intelligence. View
  30. Narawade V, Dandekar A. Soft Computing and Signal Processing. View
  31. Gyftopoulos S, Drosatos G, Pecchia L, Fico G, Kaldoudi E. MEDICON’23 and CMBEBIH’23. View
  32. Dufty N. Major Incidents, Pandemics and Mental Health. View
  33. Alhuwail D, Alhouti A. Resilient Health. View