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

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1481) Infodemiology and Infoveillance (1269) JMIR Theme Issue: COVID-19 Special Issue (2388) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1552) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1010)

Published on in Vol 6, No 2 (2020): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19447, first published .
Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends

Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends

Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends

Authors of this article:

May Oo Lwin1 Author Orcid Image ;   Jiahui Lu2 Author Orcid Image ;   Anita Sheldenkar1 Author Orcid Image ;   Peter Johannes Schulz3 Author Orcid Image ;   Wonsun Shin4 Author Orcid Image ;   Raj Gupta5 Author Orcid Image ;   Yinping Yang5 Author Orcid Image
Article Authors Cited by (282) Tweetations (9) Metrics

Journals

  1. Chivers B, Garad R, Boyle J, Skouteris H, Teede H, Harrison C. Perinatal Distress During COVID-19: Thematic Analysis of an Online Parenting Forum. Journal of Medical Internet Research 2020;22(9):e22002 View
  2. Al-Rawi A, Shukla V. Bots as Active News Promoters: A Digital Analysis of COVID-19 Tweets. Information 2020;11(10):461 View
  3. Brown S, Rhee J, Guha A, Rao V. Innovation in Precision Cardio-Oncology During the Coronavirus Pandemic and Into a Post-pandemic World. Frontiers in Cardiovascular Medicine 2020;7 View
  4. Xue J, Chen J, Chen C, Zheng C, Li S, Zhu T, Zhao J. Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter. PLOS ONE 2020;15(9):e0239441 View
  5. 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
  6. Villapol S. Gastrointestinal symptoms associated with COVID-19: impact on the gut microbiome. Translational Research 2020;226:57 View
  7. Dalili Shoaei M, Dastani M. The Role of Twitter During the COVID-19 Crisis: A Systematic Literature Review. Acta Informatica Pragensia 2020;9(2):154 View
  8. Da T, Yang L. Local COVID-19 Severity and Social Media Responses: Evidence From China. IEEE Access 2020;8:204684 View
  9. SALAMEH P, HAJJ A, BADRO D, ABOU SELWAN C, AOUN R, SACRE H. Mental Health Outcomes of the COVID-19 Pandemic and a Collapsing Economy: Perspectives from a Developing Country. Psychiatry Research 2020;294:113520 View
  10. 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
  11. Boon-Itt S, Skunkan Y. Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study. JMIR Public Health and Surveillance 2020;6(4):e21978 View
  12. Ojo A, Guntuku S, Zheng M, Beidas R, Ranney M. How Health Care Workers Wield Influence Through Twitter Hashtags: Retrospective Cross-sectional Study of the Gun Violence and COVID-19 Public Health Crises. JMIR Public Health and Surveillance 2021;7(1):e24562 View
  13. 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
  14. Jiang P, Klemeš J, Fan Y, Fu X, Bee Y. More Is Not Enough: A Deeper Understanding of the COVID-19 Impacts on Healthcare, Energy and Environment Is Crucial. International Journal of Environmental Research and Public Health 2021;18(2):684 View
  15. 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
  16. Lamsal R. Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence 2020 View
  17. Chang W. The influences of the COVID-19 pandemic on medical service behaviors. Taiwanese Journal of Obstetrics and Gynecology 2020;59(6):821 View
  18. 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
  19. DePaul A. How to shift into COVID-19 research. Nature 2020 View
  20. Chou W, Budenz A. Considering Emotion in COVID-19 Vaccine Communication: Addressing Vaccine Hesitancy and Fostering Vaccine Confidence. Health Communication 2020;35(14):1718 View
  21. Pellert M, Lasser J, Metzler H, Garcia D. Dashboard of Sentiment in Austrian Social Media During COVID-19. Frontiers in Big Data 2020;3 View
  22. Stella M. Cognitive Network Science Reconstructs How Experts, News Outlets and Social Media Perceived the COVID-19 Pandemic. Systems 2020;8(4):38 View
  23. Murlimanju B, Mishra R, Mohan R, Kosagi S, Agrawal A. Letter to the Editor Regarding: “A Surprise Sabbatical: How Mayo Clinic Neurosurgery Coped with Coronavirus Disease 2019”. World Neurosurgery 2020;144:328 View
  24. Chen N, Zhong Z, Pang J. An Exploratory Study of COVID-19 Information on Twitter in the Greater Region. Big Data and Cognitive Computing 2021;5(1):5 View
  25. Alamoodi A, Zaidan B, Zaidan A, Albahri O, Mohammed K, Malik R, Almahdi E, Chyad M, Tareq Z, Albahri A, Hameed H, Alaa M. Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: A systematic review. Expert Systems with Applications 2021;167:114155 View
  26. Lyu J, Luli G. Understanding the Public Discussion About the Centers for Disease Control and Prevention During the COVID-19 Pandemic Using Twitter Data: Text Mining Analysis Study. Journal of Medical Internet Research 2021;23(2):e25108 View
  27. S.V. P, Ittamalla R. An analysis of attitude of general public toward COVID-19 crises – sentimental analysis and a topic modeling study. Information Discovery and Delivery 2021;49(3):240 View
  28. de Melo T, Figueiredo C. Comparing News Articles and Tweets About COVID-19 in Brazil: Sentiment Analysis and Topic Modeling Approach. JMIR Public Health and Surveillance 2021;7(2):e24585 View
  29. Geronikolou S, Chrousos G. COVID-19–Induced Fear in Infoveillance Studies: Pilot Meta-analysis Study of Preliminary Results. JMIR Formative Research 2021;5(2):e21156 View
  30. Fingerman K, Ng Y, Zhang S, Britt K, Colera G, Birditt K, Charles S, Carr D. Living Alone During COVID-19: Social Contact and Emotional Well-being Among Older Adults. The Journals of Gerontology: Series B 2021;76(3):e116 View
  31. Zhang C, Xu S, Li Z, Hu S. Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study. Journal of Medical Internet Research 2021;23(3):e26482 View
  32. 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
  33. 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
  34. Ryu S, Park I, Kim M, Lee Y, Lee J, Kim H, Jhon M, Kim J, Lee J, Kim J, Kim S, Nishi A. Network study of responses to unusualness and psychological stress during the COVID-19 outbreak in Korea. PLOS ONE 2021;16(2):e0246894 View
  35. Schück S, Foulquié P, Mebarki A, Faviez C, Khadhar M, Texier N, Katsahian S, Burgun A, Chen X. Concerns Discussed on Chinese and French Social Media During the COVID-19 Lockdown: Comparative Infodemiology Study Based on Topic Modeling. JMIR Formative Research 2021;5(4):e23593 View
  36. Priadana A, Tahalea S. Hashtag activism and message frames: social network analysis of Instagram during the COVID-19 pandemic outbreak in Indonesia. Journal of Physics: Conference Series 2021;1836(1):012031 View
  37. Yu S, Eisenman D, Han Z. Temporal Dynamics of Public Emotions During the COVID-19 Pandemic at the Epicenter of the Outbreak: Sentiment Analysis of Weibo Posts From Wuhan. Journal of Medical Internet Research 2021;23(3):e27078 View
  38. Caulfield T, Bubela T, Kimmelman J, Ravitsky V, Blais J. Let’s do better: public representations of COVID-19 science. FACETS 2021;6(1):403 View
  39. Chum A, Nielsen A, Bellows Z, Farrell E, Durette P, Banda J, Cupchik G. Changes in Public Response Associated With Various COVID-19 Restrictions in Ontario, Canada: Observational Infoveillance Study Using Social Media Time Series Data. Journal of Medical Internet Research 2021;23(8):e28716 View
  40. Yousefinaghani S, Dara R, Mubareka S, Sharif S. Prediction of COVID-19 Waves Using Social Media and Google Search: A Case Study of the US and Canada. Frontiers in Public Health 2021;9 View
  41. 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
  42. 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
  43. Feng S, Kirkley A. Integrating online and offline data for crisis management: Online geolocalized emotion, policy response, and local mobility during the COVID crisis. Scientific Reports 2021;11(1) View
  44. Ng L, Carley K. “The coronavirus is a bioweapon”: classifying coronavirus stories on fact-checking sites. Computational and Mathematical Organization Theory 2021;27(2):179 View
  45. Shah A, Naqvi R, Jeong O. Detecting Topic and Sentiment Trends in Physician Rating Websites: Analysis of Online Reviews Using 3-Wave Datasets. International Journal of Environmental Research and Public Health 2021;18(9):4743 View
  46. Ismael F, Bizario J, Battagin T, Zaramella B, Leal F, Torales J, Ventriglio A, Marziali M, Martins S, Castaldelli-Maia J. Post-infection depressive, anxiety and post-traumatic stress symptoms: A prospective cohort study in patients with mild COVID-19. Progress in Neuro-Psychopharmacology and Biological Psychiatry 2021;111:110341 View
  47. Mwendwa P, Githui S, Marete E, Kroll T. COVID-19 and vaccines in Africa: a descriptive and thematic analysis of Twitter content. HRB Open Research 2021;4:43 View
  48. Jong W, Liang O, Yang C. The Exchange of Informational Support in Online Health Communities at the Onset of the COVID-19 Pandemic: Content Analysis. JMIRx Med 2021;2(3):e27485 View
  49. Herbstreit F, Overbeck M, Berger M, Skarabis A, Brenner T, Schmidt K. Characteristics of Critically Ill Patients with COVID-19 Compared to Patients with Influenza—A Single Center Experience. Journal of Clinical Medicine 2021;10(10):2056 View
  50. Jiang Y, Huang X, Li Z. Spatiotemporal Patterns of Human Mobility and Its Association with Land Use Types during COVID-19 in New York City. ISPRS International Journal of Geo-Information 2021;10(5):344 View
  51. Kumar V, Singh D, Kaur M, Damaševičius R. Overview of current state of research on the application of artificial intelligence techniques for COVID-19. PeerJ Computer Science 2021;7:e564 View
  52. Altan A. Emotional effect of the Covid-19 pandemic on oral surgery procedures: a social media analysis. Journal of Dental Anesthesia and Pain Medicine 2021;21(3):237 View
  53. Pollack C, Gilbert-Diamond D, Alford-Teaster J, Onega T. A Longitudinal Evaluation of the Language and Sentiment About Telemedicine and COVID-19 on Twitter: Infodemiology Study (Preprint). Journal of Medical Internet Research 2021 View
  54. Schweinberger M, Haugh M, Hames S. Analysing discourse around COVID-19 in the Australian Twittersphere: A real-time corpus-based analysis. Big Data & Society 2021;8(1):205395172110214 View
  55. Ilyas H, Anwar A, Yaqub U, Alzamil Z, Appelbaum D. Analysis and visualization of COVID-19 discourse on Twitter using data science: a case study of the USA, the UK and India. Global Knowledge, Memory and Communication 2022;71(3):140 View
  56. Velásquez N, Leahy R, Restrepo N, Lupu Y, Sear R, Gabriel N, Jha O, Goldberg B, Johnson N. Online hate network spreads malicious COVID-19 content outside the control of individual social media platforms. Scientific Reports 2021;11(1) View
  57. Sanders J, Tosi A, Obradovic S, Miligi I, Delaney L. Lessons From the UK's Lockdown: Discourse on Behavioural Science in Times of COVID-19. Frontiers in Psychology 2021;12 View
  58. Nanath K, Joy G. Leveraging Twitter data to analyze the virality of Covid-19 tweets: a text mining approach. Behaviour & Information Technology 2023;42(2):196 View
  59. Cohrdes C, Yenikent S, Wu J, Ghanem B, Franco-Salvador M, Vogelgesang F. Indications of Depressive Symptoms During the COVID-19 Pandemic in Germany: Comparison of National Survey and Twitter Data. JMIR Mental Health 2021;8(6):e27140 View
  60. Miller M, Romine W, Oroszi T. Public Discussion of Anthrax on Twitter: Using Machine Learning to Identify Relevant Topics and Events. JMIR Public Health and Surveillance 2021;7(6):e27976 View
  61. Hanschmidt F, Kersting A. Emotions in Covid-19 Twitter discourse following the introduction of social contact restrictions in Central Europe. Journal of Public Health 2023;31(6):933 View
  62. Kwan J, Henry M, Christophers B, Tamirisa K, Thamman R, Sadler D, Aggarwal N, Cheng R, Parwani P, Dent S, Ismail-Khan R, Fradley M, Brown S. The Role and Impact of Social Media in Cardio-oncology During the COVID-19 Pandemic. Current Oncology Reports 2021;23(8) View
  63. Li Y, Luan S, Li Y, Hertwig R. Changing emotions in the COVID-19 pandemic: A four-wave longitudinal study in the United States and China. Social Science & Medicine 2021;285:114222 View
  64. Marzouki A, Chouikh A, Mellouli S, Haddad R. From Sustainable Development Goals to Sustainable Cities: A Social Media Analysis for Policy-Making Decision. Sustainability 2021;13(15):8136 View
  65. Ahmad W, Wang B, Xu H, Xu M, Zeng Z. Topics, Sentiments, and Emotions Triggered by COVID-19-Related Tweets from IRAN and Turkey Official News Agencies. SN Computer Science 2021;2(5) View
  66. Hammes L, Rossi A, Pedrotti L, Pitrez P, Mutlaq M, Rosa R. Is the press properly presenting the epidemiological data on COVID-19? An analysis of newspapers from 25 countries. Journal of Public Health Policy 2021;42(3):359 View
  67. 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
  68. Tan H, Peng S, Zhu C, You Z, Miao M, Kuai S. Long-term Effects of the COVID-19 Pandemic on Public Sentiments in Mainland China: Sentiment Analysis of Social Media Posts. Journal of Medical Internet Research 2021;23(8):e29150 View
  69. Pan Y, Zhang L, Yan Z, Lwin M, Skibniewski M. Discovering optimal strategies for mitigating COVID-19 spread using machine learning: Experience from Asia. Sustainable Cities and Society 2021;75:103254 View
  70. Gourisaria M, Chandra S, Das H, Patra S, Sahni M, Leon-Castro E, Singh V, Kumar S. Semantic Analysis and Topic Modelling of Web-Scrapped COVID-19 Tweet Corpora through Data Mining Methodologies. Healthcare 2022;10(5):881 View
  71. Santoveña-Casal S, Pérez M. Relevance of E-Participation in the state health campaign in Spain: #EstoNoEsUnJuego / #ThisIsNotAGame. Technology in Society 2022;68:101877 View
  72. Gutub A, Shambour M, Abu-Hashem M. Coronavirus impact on human feelings during 2021 Hajj season via deep learning critical Twitter analysis. Journal of Engineering Research 2023;11(1):100001 View
  73. Photiou A, Nicolaides C, Dhillon P. Social status and novelty drove the spread of online information during the early stages of COVID-19. Scientific Reports 2021;11(1) View
  74. Frąckowiak-Sochańska M, Mroczkowska D, Kubacka M. Dynamika i kontekst doświadczeń emocjonalnych pracujących zawodowo rodziców w czasie pandemii COVID-19. Przegląd Socjologii Jakościowej 2022;18(4):118 View
  75. Xu W, Tshimula J, Dubé È, Graham J, Greyson D, MacDonald N, Meyer S. Unmasking the Twitter Discourses on Masks During the COVID-19 Pandemic: User Cluster–Based BERT Topic Modeling Approach. JMIR Infodemiology 2022;2(2):e41198 View
  76. Chang V, Ng C, Xu Q, Guizani M, Hossain M. How Do People View COVID-19 Vaccines. Journal of Global Information Management 2022;30(10):1 View
  77. Nakagawa K, Yang N, Wilson M, Yellowlees P. Twitter Usage Among Physicians From 2016 to 2020: Algorithm Development and Longitudinal Analysis Study. Journal of Medical Internet Research 2022;24(9):e37752 View
  78. Ng C, Wong E, Ho K, Cheung A, Wong S, Yeoh E. Association between Information Dissemination and Compliance with Preventive Measures during the Coronavirus Disease Pandemic in Hong Kong Working Population: Cross-Sectional Survey. Challenges 2022;13(1):17 View
  79. Kang Y, McCosker A, Kamstra P, Farmer J. Resilience in Web-Based Mental Health Communities: Building a Resilience Dictionary With Semiautomatic Text Analysis. JMIR Formative Research 2022;6(9):e39013 View
  80. Shehata W, Abdeldaim D. Social media and spreading panic among adults during the COVID-19 pandemic, Egypt. Environmental Science and Pollution Research 2022;29(16):23374 View
  81. Zheng H, Goh D, Lee E, Lee C, Theng Y. Understanding the effects of message cues on COVID‐19 information sharing on Twitter. Journal of the Association for Information Science and Technology 2022;73(6):847 View
  82. Huang Z, Tay E, Wee D, Guo H, Lim H, Chow A. Public Perception of the Use of Digital Contact-Tracing Tools After the COVID-19 Lockdown: Sentiment Analysis and Opinion Mining. JMIR Formative Research 2022;6(3):e33314 View
  83. Yin J, Kim E, Hwang Y. Changes in residents’ attitudes toward tourism and perceptions of tourism contribution pre- and peri-Covid-19 pandemic: role of perceived gratitude and damage. Asia Pacific Journal of Tourism Research 2022;27(6):637 View
  84. AYTEKİN Ç, GULMAMMADZADA U, AGHAYEV H. Covid-19 Aşı Karşıtlığı Tutumunda Çok Yüksek Etkileşime Sahip Trollerin Ortak Özelliklerini Belirlemeye İlişkin Bir Araştırma. Türkiye İletişim Araştırmaları Dergisi 2023;(42):19 View
  85. Tan E, Wee R, Saw Y, Heng K, Chin J, Tong E, Liu J. Tracking Private WhatsApp Discourse About COVID-19 in Singapore: Longitudinal Infodemiology Study. Journal of Medical Internet Research 2021;23(12):e34218 View
  86. Liu Y, Yin Z, Ni C, Yan C, Wan Z, Malin B. Examining Rural and Urban Sentiment Difference in COVID-19–Related Topics on Twitter: Word Embedding–Based Retrospective Study. Journal of Medical Internet Research 2023;25:e42985 View
  87. Lin B, Zou L, Duffield N, Mostafavi A, Cai H, Zhou B, Tao J, Yang M, Mandal D, Abedin J. Revealing the linguistic and geographical disparities of public awareness to Covid-19 outbreak through social media. International Journal of Digital Earth 2022;15(1):868 View
  88. Kong X, Jin Y, Liu L, Xu J. Firms' exposures on COVID-19 and stock price crash risk: Evidence from China. Finance Research Letters 2023;52:103562 View
  89. Usher K, Durkin J, Martin S, Vanderslott S, Vindrola-Padros C, Usher L, Jackson D. Public Sentiment and Discourse on Domestic Violence During the COVID-19 Pandemic in Australia: Analysis of Social Media Posts. Journal of Medical Internet Research 2021;23(10):e29025 View
  90. Zhou Y, Xu J, Yin M, Zeng J, Ming H, Wang Y. Spatial-Temporal Pattern Evolution of Public Sentiment Responses to the COVID-19 Pandemic in Small Cities of China: A Case Study Based on Social Media Data Analysis. International Journal of Environmental Research and Public Health 2022;19(18):11306 View
  91. Wankhade M, Rao A. Opinion analysis and aspect understanding during covid-19 pandemic using BERT-Bi-LSTM ensemble method. Scientific Reports 2022;12(1) View
  92. 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
  93. Santoveña-Casal S, Gil-Quintana J, Ramos L. Digital citizens’ feelings in national #Covid 19 campaigns in Spain. Heliyon 2021;7(10):e08112 View
  94. Ishida T, Seki Y, Kashino W, Kando N. Extracting Citizen Feedback from Social Media by Appraisal Opinion Type Viewpoint. Journal of Natural Language Processing 2022;29(2):416 View
  95. Al-Garadi M, Yang Y, Sarker A. The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges. Healthcare 2022;10(11):2270 View
  96. Lwin M, Sheldenkar A, Lu J, Schulz P, Shin W, Panchapakesan C, Gupta R, Yang Y. The Evolution of Public Sentiments During the COVID-19 Pandemic: Case Comparisons of India, Singapore, South Korea, the United Kingdom, and the United States. JMIR Infodemiology 2022;2(1):e31473 View
  97. Smith M, Blakemore J, Ho J, Grifo J. Making it (net)work: a social network analysis of “fertility” in Twitter before and during the COVID-19 pandemic. F&S Reports 2021;2(4):472 View
  98. Reshetnikov A, Prisyazhnaya N, Steger F, Pavlov S, Vyatkina N. Features of Social Behavior and the Awareness of Moscow Residents about COVID-19 at the Beginning of the Pandemic. Social Sciences 2022;12(1):25 View
  99. Mathayomchan B, Taecharungroj V, Wattanacharoensil W. Evolution of COVID-19 tweets about Southeast Asian Countries: topic modelling and sentiment analyses. Place Branding and Public Diplomacy 2023;19(3):317 View
  100. Alagarsamy S, Mehrolia S, Pushparaj U, Jeevananda S. Explaining the intention to uptake COVID-19 vaccination using the behavioral and social drivers of vaccination (BeSD) model. Vaccine: X 2022;10:100140 View
  101. Saquete E, Zubcoff J, Gutiérrez Y, Martínez-Barco P, Fernández J. Why are some social-media contents more popular than others? Opinion and association rules mining applied to virality patterns discovery. Expert Systems with Applications 2022;197:116676 View
  102. Umair A, Masciari E. Sentimental and spatial analysis of COVID-19 vaccines tweets. Journal of Intelligent Information Systems 2023;60(1):1 View
  103. Tsao S, MacLean A, Chen H, Li L, Yang Y, Butt Z. Public Attitudes During the Second Lockdown: Sentiment and Topic Analyses Using Tweets From Ontario, Canada. International Journal of Public Health 2022;67 View
  104. Jain V, Kashyap K. Ensemble hybrid model for Hindi COVID-19 text classification with metaheuristic optimization algorithm. Multimedia Tools and Applications 2023;82(11):16839 View
  105. Patel R, Smeraldi F, Abdollahyan M, Irving J, Bessant C. Analysis of mental and physical disorders associated with COVID-19 in online health forums: a natural language processing study. BMJ Open 2021;11(11):e056601 View
  106. TUNA N, SEBATLI SAĞLAM A, ÇAVDUR F. Covid-19 Salgını ile İlgili Paylaşımlar Üzerinde Veri Analizi. Bilişim Teknolojileri Dergisi 2022;15(1):13 View
  107. Babić K, Petrović M, Beliga S, Martinčić-Ipšić S, Matešić M, Meštrović A. Characterisation of COVID-19-Related Tweets in the Croatian Language: Framework Based on the Cro-CoV-cseBERT Model. Applied Sciences 2021;11(21):10442 View
  108. Shi B, Xu K, Zhao J. The long-term impacts of air quality on fine-grained online emotional responses to haze pollution in 160 Chinese cities. Science of The Total Environment 2023;864:161160 View
  109. Pathak T, Athavale H, Pathak A, Athavale S. Sentiments Evoked by WHO Public Health Posts During the COVID-19 Pandemic: A Neural Network-Based Machine Learning Analysis. Cureus 2021 View
  110. Zhou Y, Li R, Shen L. Targeting COVID-19 vaccine-hesitancy in college students: An audience-centered approach. Journal of American College Health 2023:1 View
  111. Golder S, Jefferson L, McHugh E, Essex H, Heathcote C, Castro Avila A, Dale V, Van Der Feltz‐Cornelis C, Bloor K. General practitioners' wellbeing during the COVID‐19 pandemic: Novel methods with social media data. Health Information & Libraries Journal 2023;40(4):400 View
  112. Liu B, Zhu J, Su F, Wen B, Wu Y. Financial Crisis in Management Stress: From the Perspective of Crisis Anxiety of Others. Frontiers in Psychology 2022;13 View
  113. Mahdikhani M. Predicting the popularity of tweets by analyzing public opinion and emotions in different stages of Covid-19 pandemic. International Journal of Information Management Data Insights 2022;2(1):100053 View
  114. Xu X, Li Z, Wang R, Zhao L. Analysis of the Evolution of User Emotion and Opinion Leaders’ Information Dissemination Behavior in the Knowledge Q&A Community during COVID-19. International Journal of Environmental Research and Public Health 2021;18(22):12252 View
  115. Kendrick K, Isaac M. Overview of behavioural and psychological consequences of COVID 19. Current Opinion in Psychiatry 2021;34(5):477 View
  116. León-Sandoval E, Zareei M, Barbosa-Santillán L, Falcón Morales L. Measuring the Impact of Language Models in Sentiment Analysis for Mexico’s COVID-19 Pandemic. Electronics 2022;11(16):2483 View
  117. Chew A, Pan Y, Wang Y, Zhang L. Hybrid deep learning of social media big data for predicting the evolution of COVID-19 transmission. Knowledge-Based Systems 2021;233:107417 View
  118. Cheng C. Time-Series Associations between Public Interest in COVID-19 Variants and National Vaccination Rate: A Google Trends Analysis. Behavioral Sciences 2022;12(7):223 View
  119. Ruiz-Núñez C, Herrera-Peco I, Campos-Soler S, Carmona-Pestaña Á, Benítez de Gracia E, Peña Deudero J, García-Notario A. Sentiment Analysis on Twitter: Role of Healthcare Professionals in the Global Conversation during the AstraZeneca Vaccine Suspension. International Journal of Environmental Research and Public Health 2023;20(3):2225 View
  120. Clemente-Suárez V, Navarro-Jiménez E, Simón-Sanjurjo J, Beltran-Velasco A, Laborde-Cárdenas C, Benitez-Agudelo J, Bustamante-Sánchez Á, Tornero-Aguilera J. Mis–Dis Information in COVID-19 Health Crisis: A Narrative Review. International Journal of Environmental Research and Public Health 2022;19(9):5321 View
  121. Suzuki R, Iizuka Y, Lefor A. COVID-19 related discrimination in Japan. Medicine 2021;100(36):e27105 View
  122. Geronikolou S, Drosatos G, Chrousos G. Emotional Analysis of Twitter Posts During the First Phase of the COVID-19 Pandemic in Greece: Infoveillance Study. JMIR Formative Research 2021;5(9):e27741 View
  123. Maheux A, Nesi J, Galla B, Roberts S, Choukas‐Bradley S. #Grateful: Longitudinal Associations Between Adolescents’ Social Media Use and Gratitude During the COVID‐19 Pandemic. Journal of Research on Adolescence 2021;31(3):734 View
  124. Pagotto D, Barbosa R, Borges C, Nassif V. Sentimentos Negativos de Empreendedores e a Covid-19: Uma Análise de Tweets. Revista Inteligência Competitiva 2022;12(1):e0414 View
  125. Zhang H, Tham J, Waheed M. The Effects of Receiving and Expressing Health Information on Social Media during the COVID-19 Infodemic: An Online Survey among Malaysians. International Journal of Environmental Research and Public Health 2022;19(13):7991 View
  126. Ock H, Seong M, Kim I. Adapting and Validating the COVID-19 Vaccine Hesitancy and Vaccine Conspiracy Beliefs Scales in Korea. Healthcare 2022;10(11):2274 View
  127. Ahmad A, Rustam F, Saad E, Siddique M, Lee E, Mansilla A, Díez I, Ashraf I, Qamar U. Analyzing preventive precautions to limit spread of COVID-19. PLOS ONE 2022;17(8):e0272350 View
  128. Liu Z, Yang J. Public Support for COVID-19 Responses: Cultural Cognition, Risk Perception, and Emotions. Health Communication 2023;38(4):648 View
  129. Pavić Ž, Šuljok A, Jurlina J. Balanced Reporting and Boomerang Effect: An Analysis of Croatian Online News Sites Vaccination Coverage and User Comments during the COVID-19 Pandemic. Vaccines 2022;10(12):2085 View
  130. Whiston A, Igou E, Fortune D. Emotion networks across self-reported depression levels during the COVID-19 pandemic. Cognition and Emotion 2022;36(1):31 View
  131. Ghanem A, Asaad C, Hafidi H, Moukafih Y, Guermah B, Sbihi N, Zakroum M, Ghogho M, Dairi M, Cherqaoui M, Baina K. Real-Time Infoveillance of Moroccan Social Media Users’ Sentiments towards the COVID-19 Pandemic and Its Management. International Journal of Environmental Research and Public Health 2021;18(22):12172 View
  132. Mwangale Kiptinness E, Okoye J, Shiri R. Media coverage of the novel Coronavirus (Covid-19) in Kenya and Tanzania: Content analysis of newspaper articles in East Africa. Cogent Medicine 2021;8(1) View
  133. Yuan L, Wang M, Umakanthan S. The emotion bias of health product consumers in the context of COVID-19. PLOS ONE 2022;17(11):e0278219 View
  134. Obreja D. Narrative communication regarding the Covid-19 vaccine: a thematic analysis of comments on Romanian official Facebook page “RO Vaccinare”. SN Social Sciences 2022;2(8) View
  135. 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. The Geography of Covid-19 Spread in Italy Using Social Media and Geospatial Data Analytics. The International Journal of Intelligence, Security, and Public Affairs 2021;23(3):228 View
  136. Vyas P, Reisslein M, Rimal B, Vyas G, Basyal G, Muzumdar P. Automated Classification of Societal Sentiments on Twitter With Machine Learning. IEEE Transactions on Technology and Society 2022;3(2):100 View
  137. Ng Q, Yau C, Lim Y, Wong L, Liew T. Public sentiment on the global outbreak of monkeypox: an unsupervised machine learning analysis of 352,182 twitter posts. Public Health 2022;213:1 View
  138. Singhal A, Baxi M, Mago V. Synergy Between Public and Private Health Care Organizations During COVID-19 on Twitter: Sentiment and Engagement Analysis Using Forecasting Models. JMIR Medical Informatics 2022;10(8):e37829 View
  139. Kubacka M, Luczys P, Modrzyk A, Stamm A. Pandemic rage: Everyday frustrations in times of the COVID-19 crisis. Current Sociology 2023;71(5):887 View
  140. Choi D. The multifaceted impact of social media on risk, behavior, and negative emotions during the COVID-19 outbreak in South Korea. Asian Journal of Communication 2021;31(5):337 View
  141. Wolaver A, Doces J. The impact of COVID‐19 and political identification on framing bias in an infectious disease experiment: The frame reigns supreme. Social Science Quarterly 2021;102(6):2459 View
  142. León-Sandoval E, Zareei M, Barbosa-Santillán L, Falcón Morales L, Pareja Lora A, Ochoa Ruiz G, Hošovský A. Monitoring the Emotional Response to the COVID-19 Pandemic Using Sentiment Analysis: A Case Study in Mexico. Computational Intelligence and Neuroscience 2022;2022:1 View
  143. Fattoh I, Kamal Alsheref F, Ead W, Youssef A, Alonso-Betanzos A. Semantic Sentiment Classification for COVID-19 Tweets Using Universal Sentence Encoder. Computational Intelligence and Neuroscience 2022;2022:1 View
  144. Wang R, Zhang H. Who spread COVID-19 (mis)information online? Differential informedness, psychological mechanisms, and intervention strategies. Computers in Human Behavior 2023;138:107486 View
  145. Zahry N, McCluskey M, Ling J. Risk governance during the COVID‐19 pandemic: A quantitative content analysis of governors' narratives on twitter. Journal of Contingencies and Crisis Management 2023;31(1):77 View
  146. ‘Ali N, Rosenberg D. Understanding the consideration of strategies for coping with locality violence in Arab society in Israel. Security Journal 2024;37(1):1 View
  147. Kyröläinen A, Luke J, Libben G, Kuperman V. Valence norms for 3,600 English words collected during the COVID-19 pandemic: Effects of age and the pandemic. Behavior Research Methods 2021;54(5):2445 View
  148. Khraisat B, Toubasi A, AlZoubi L, Al-Sayegh T, Mansour A. Meta-analysis of prevalence: the psychological sequelae among COVID-19 survivors. International Journal of Psychiatry in Clinical Practice 2022;26(3):234 View
  149. Monzani D, Vergani L, Pizzoli S, Marton G, Pravettoni G. Emotional Tone, Analytical Thinking, and Somatosensory Processes of a Sample of Italian Tweets During the First Phases of the COVID-19 Pandemic: Observational Study. Journal of Medical Internet Research 2021;23(10):e29820 View
  150. Zhang Q, Yi G, Chen L, He W, Kaddoura S. Sentiment analysis and causal learning of COVID-19 tweets prior to the rollout of vaccines. PLOS ONE 2023;18(2):e0277878 View
  151. Huang C, Bandyopadhyay A, Fan W, Miller A, Gilbertson-White S, Chen Z. Mental toll on working women during the COVID-19 pandemic: An exploratory study using Reddit data. PLOS ONE 2023;18(1):e0280049 View
  152. Beliga S, Martinčić-Ipšić S, Matešić M, Petrijevčanin Vuksanović I, Meštrović A. Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing. JMIR Public Health and Surveillance 2021;7(12):e31540 View
  153. Stevens H, Rasul M, Oh Y. Emotions and Incivility in Vaccine Mandate Discourse: Natural Language Processing Insights. JMIR Infodemiology 2022;2(2):e37635 View
  154. Parthasarathi , Kumari G. Religious Tweets During COVID-19: Qualitative Analysis of Articulation of Ideas of Netizens. Media Watch 2022;13(1):104 View
  155. Lee E, Zheng H, Goh D, Lee C, Theng Y. Examining COVID-19 Tweet Diffusion Using an Integrated Social Amplification of Risk and Issue-Attention Cycle Framework. Health Communication 2024;39(3):493 View
  156. 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
  157. Jabeen A, Afzal S, Maqsood M, Mehmood I, Yasmin S, Tabish Niaz M, Nam Y. An LSTM Based Forecasting for Major Stock Sectors Using COVID Sentiment. Computers, Materials & Continua 2021;67(1):1191 View
  158. Pourkarim M, Nayebzadeh S, Alavian S, Hataminasab S. Digital Marketing: A Unique Multidisciplinary Approach towards the Elimination of Viral Hepatitis. Pathogens 2022;11(6):626 View
  159. Zhang W, Li L, Mou J, Zhang M, Cheng X, Xia H. Mediating Effects of Attitudes, Risk Perceptions, and Negative Emotions on Coping Behaviors. Journal of Organizational and End User Computing 2022;34(6):1 View
  160. Pelegrín-Borondo J, Arias-Oliva M, Almahameed A, Prado Román M. Covid-19 vaccines: A model of acceptance behavior in the healthcare sector. European Research on Management and Business Economics 2021;27(3):100171 View
  161. Mazzuca C, Falcinelli I, Michalland A, Tummolini L, Borghi A. Differences and similarities in the conceptualization of COVID-19 and other diseases in the first Italian lockdown. Scientific Reports 2021;11(1) View
  162. Hopkins S, Stark A, Zinoviev D, Tousignant O, Fireman G. College student expression on Twitter during the COVID-19 pandemic. Journal of American College Health 2024;72(3):722 View
  163. Choi R, Nagappan A, Kopyto D, Wexler A. Pregnant at the start of the pandemic: a content analysis of COVID-19-related posts on online pregnancy discussion boards. BMC Pregnancy and Childbirth 2022;22(1) View
  164. Houlden S, Hodson J, Veletsianos G, Thompson C, Reid D. Inoculating an Infodemic: An Ecological Approach to Understanding Engagement With COVID-19 Online Information. American Behavioral Scientist 2021;65(14):1990 View
  165. Nguyen H, Tsolak D, Karmann A, Knauff S, Kühne S. Efficient and Reliable Geocoding of German Twitter Data to Enable Spatial Data Linkage to Official Statistics and Other Data Sources. Frontiers in Sociology 2022;7 View
  166. Altan H, Coşgun A. Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study. BMC Oral Health 2021;21(1) View
  167. Xu H, Liu R, Luo Z, Xu M. COVID-19 vaccine sensing: Sentiment analysis and subject distillation from twitter data. Telematics and Informatics Reports 2022;8:100016 View
  168. Houlden S, Veletsianos G, Hodson J, Reid D, Thompson C. COVID-19 health misinformation: using design-based research to develop a theoretical framework for intervention. Health Education 2022;122(5):506 View
  169. F. Ibrahim A, Hassaballah M, A. Ali A, Nam Y, A. Ibrahim I. COVID19 Outbreak: A Hierarchical Framework for User Sentiment Analysis. Computers, Materials & Continua 2022;70(2):2507 View
  170. Kada A, Chouikh A, Mellouli S, Prashad A, Straus S, Fahim C, Gaito S. An exploration of Canadian government officials’ COVID-19 messages and the public’s reaction using social media data. PLOS ONE 2022;17(9):e0273153 View
  171. Fernandez G, Maione C, Yang H, Zaballa K, Bonnici N, Carter J, Spitzberg B, Jin C, Tsou M. Social Network Analysis of COVID-19 Sentiments: 10 Metropolitan Cities in Italy. International Journal of Environmental Research and Public Health 2022;19(13):7720 View
  172. Drescher L, Roosen J, Aue K, Dressel K, Schär W, Götz A. The Spread of COVID-19 Crisis Communication by German Public Authorities and Experts on Twitter: Quantitative Content Analysis. JMIR Public Health and Surveillance 2021;7(12):e31834 View
  173. Jain V, Kashyap K. Multilayer hybrid ensemble machine learning model for analysis of Covid-19 vaccine sentiments. Journal of Intelligent & Fuzzy Systems 2022;43(5):6307 View
  174. Waggoner P, Shapiro R, Frederick S, Gong M. Uncovering the Online Social Structure Surrounding COVID-19. Journal of Social Computing 2021;2(2):157 View
  175. Karabin M, Kyröläinen A, Kuperman V. Increase in Linguistic Complexity in Older Adults During COVID-19. Experimental Aging Research 2024;50(3):312 View
  176. Rosato C, Moore R, Carter M, Heap J, Harris J, Storopoli J, Maskell S. Extracting Self-Reported COVID-19 Symptom Tweets and Twitter Movement Mobility Origin/Destination Matrices to Inform Disease Models. Information 2023;14(3):170 View
  177. Chen S, Yin S, Guo Y, Ge Y, Janies D, Dulin M, Brown C, Robinson P, Zhang D. Content and sentiment surveillance (CSI): A critical component for modeling modern epidemics. Frontiers in Public Health 2023;11 View
  178. Xie T, Ge Y, Xu Q, Chen S. Public Awareness and Sentiment Analysis of COVID-Related Discussions Using BERT-Based Infoveillance. AI 2023;4(1):333 View
  179. Handayani P, Zagatti G, Kefi H, Bressan S. Impact of Social Media Usage on Users’ COVID-19 Protective Behavior: Survey Study in Indonesia. JMIR Formative Research 2023;7:e46661 View
  180. Amores J, Blanco-Herrero D, Arcila-Calderón C. The Conversation around COVID-19 on Twitter—Sentiment Analysis and Topic Modelling to Analyse Tweets Published in English during the First Wave of the Pandemic. Journalism and Media 2023;4(2):467 View
  181. Muitana G, Amato C. Topics, concerns, and feelings commented on Facebook after the first death by COVID-19 in Mozambique. Revista de Investigación e Innovación en Ciencias de la Salud 2023;5(1):press View
  182. Sukhavasi N, Misra J, Kaulgud V, Podder S. Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19. Journal of Computational Social Science 2023;6(2):411 View
  183. Anoop V, Sreelakshmi S. Public discourse and sentiment during Mpox outbreak: an analysis using natural language processing. Public Health 2023;218:114 View
  184. Robinson J. Global health, global networks: a multilingual network approach to COVID-19 tweets in Norway, Korea, and Italy. Health & New Media Research 2022;6(2):174 View
  185. Das D, Pal S, Jena L. Emotional Labour During the COVID-19 Pandemic—Current Inquiry and Suggested Future Research Directions. Management and Labour Studies 2023;48(4):560 View
  186. Guo Y, Hou Y, Xiang H, Chen L. “Help Us!”: a content analysis of COVID-19 help-seeking posts on Weibo during the first lockdown. BMC Public Health 2023;23(1) View
  187. Mao L, Chu E, Gu J, Hu T, Weiner B, Su Y. A 4D Theoretical Framework for Measuring Topic-Specific Influence on Twitter: Development and Usability Study on Dietary Sodium Tweets. Journal of Medical Internet Research 2023;25:e45897 View
  188. Shokoohyar S, Ghomi V, Jafari Gorizi A, Liang W, Sinclair A. Impact of COVID-19 outbreak and vaccination on ride-sharing services: a social media analysis. Transportation Letters 2024;16(6):527 View
  189. GÜNDÜZ HOŞGÖR D, GÜNGÖRDÜ H, HOŞGÖR H. COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ. R&S - Research Studies Anatolia Journal 2023;6(3):267 View
  190. Lee J, Kalny C, Demetriades S, Walter N. Angry Content for Angry People: How Anger Appeals Facilitate Health Misinformation Recall on Social Media. Media Psychology 2023:1 View
  191. Elliott J, Tong C, Gregg S, Mallinson S, Giguere A, Brierley M, Giosa J, MacNeil M, Juzwishin D, Sims-Gould J, Rockwood K, Stolee P. Policy and practices in primary care that supported the provision and receipt of care for older persons during the COVID-19 pandemic: a qualitative case study in three Canadian provinces. BMC Primary Care 2023;24(1) View
  192. Alvarez-Mon M, Pereira-Sanchez V, Hooker E, Sanchez F, Alvarez-Mon M, Teo A. Content and User Engagement of Health-Related Behavior Tweets Posted by Mass Media Outlets From Spain and the United States Early in the COVID-19 Pandemic: Observational Infodemiology Study. JMIR Infodemiology 2023;3:e43685 View
  193. Li Y, Huang S, Wei J, Brindle T, Lee C. What captures attention in the risk communication process: Exploring streaming video attractiveness during the first wave of the COVID-19 pandemic in China. Computers in Human Behavior 2023;149:107909 View
  194. Rodrigues P, Borges A, Brochado A, Sousa A. COVID-19 vaccine hesitation and brand choice uncertainty. International Journal of Pharmaceutical and Healthcare Marketing 2023;17(4):495 View
  195. Scharnetzki E, Waterston L, Scherer A, Thorpe A, Fagerlin A, Han P. Effects of Prosocial and Hope-Promoting Communication Strategies on COVID-19 Worry and Intentions for Risk-Reducing Behaviors and Vaccination: Experimental Study. JMIR Formative Research 2023;7:e41959 View
  196. Song L, Zhang A, Hu Z. Greenspace exposure is conducive to the resilience of public sentiment during the COVID-19 pandemic. Health & Place 2023;83:103096 View
  197. Fleury-Bahi G, Sapin A, Navarro O, Boudoukha A, Galharret J, Bret A, Congard A. Willingness to be vaccinated against COVID-19: the role of risk perception, trust in institutions, and affects. Frontiers in Psychology 2023;14 View
  198. Gao J, Gallegos G, West J. Public Health Policy, Political Ideology, and Public Emotion Related to COVID-19 in the U.S. International Journal of Environmental Research and Public Health 2023;20(21):6993 View
  199. Khakimova A, Zolotarev O, Sharma B, Agrawal S, Jain S. Methods for Assessing the Psychological Tension of Social Network Users during the Coronavirus Pandemic and Its Uses for Predictive Analysis. Sustainability 2023;15(13):10008 View
  200. Shankar K, Chandrasekaran R, Jeripity Venkata P, Miketinas D. Investigating the Role of Nutrition in Enhancing Immunity During the COVID-19 Pandemic: Twitter Text-Mining Analysis. Journal of Medical Internet Research 2023;25:e47328 View
  201. Stefanis C, Giorgi E, Kalentzis K, Tselemponis A, Nena E, Tsigalou C, Kontogiorgis C, Kourkoutas Y, Chatzak E, Dokas I, Constantinidis T, Bezirtzoglou E. Sentiment analysis of epidemiological surveillance reports on COVID-19 in Greece using machine learning models. Frontiers in Public Health 2023;11 View
  202. Beierle F, Pryss R, Aizawa A. Sentiments about Mental Health on Twitter—Before and during the COVID-19 Pandemic. Healthcare 2023;11(21):2893 View
  203. Luan Y, Sun L, Luo F, Stillwell D. Public emotional responses to crisis: The COVID‐19 pandemic in Wuhan and London. Social and Personality Psychology Compass 2023;17(8) View
  204. Isip Tan I, Cleofas J, Solano G, Pillejera J, Catapang J. Interdisciplinary Approach to Identify and Characterize COVID-19 Misinformation on Twitter: Mixed Methods Study. JMIR Formative Research 2023;7:e41134 View
  205. Drescher L, Roosen J, Aue K, Dressel K, Schär W, Götz A. Emotionalität in der COVID-19-Krisenkommunikation von Behörden und unabhängigen Expert*innen auf Twitter. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz 2023;66(6):689 View
  206. Weerasinghe S, Oyebode O, Orji R, Matwin S. Dynamics of emotion trends in Canadian Twitter users during COVID-19 confinement in relation to caseloads: Artificial intelligence-based emotion detection approach. DIGITAL HEALTH 2023;9:205520762311714 View
  207. Moitra S, Anderson A, Eathorne A, Brickstock A, Adan A, Akgün M, Tabrizi A, Haldar P, Henderson L, Jindal A, Jindal S, Kerget B, Khadour F, Melenka L, Moitra S, Moitra T, Mukherjee R, Murgia N, Semprini A, Turner A, Lacy P. COVID-19 infodemic and health-related quality of life in patients with chronic respiratory diseases: A multicentre, observational study. Journal of Global Health 2023;13 View
  208. Lu Y. Disease, Scapegoating, and Social Contexts: Examining Social Contexts of the Support for Racist Naming of COVID-19 on Twitter. Journal of Health and Social Behavior 2023 View
  209. Kyröläinen A, Kuperman V. Emotional State of Older Adults During the COVID-19 Pandemic: Insights from the Cognitive and Social Well-Being (CoSoWELL) Corpus. Experimental Aging Research 2024;50(4):482 View
  210. Kodati D, Dasari C. Negative emotion detection on social media during the peak time of COVID-19 through deep learning with an auto-regressive transformer. Engineering Applications of Artificial Intelligence 2024;127:107361 View
  211. Rupar M, Bobowik M, Sekerdej M, Pastor E, Kołeczek M, Jamróz‐Dolińska K, Ghorbani F, Mari S. The link between anger and admiration toward governmental actions and self‐reported preventive behaviour in the context of the COVID‐19 pandemic. International Journal of Psychology 2024;59(1):172 View
  212. Nguyen D, Phung T. Media Credibility and Re-use Intention for Information Seeking in Crisis: A Case of Cross-Platform Media Complementary Effect in Covid-19 Pandemic in Vietnam. SAGE Open 2023;13(4) View
  213. Grabe M, Brown D, Ochieng J, Bryden J, Robinson R, Ahn Y, Moss A, Wang W. The Social Contagion Potential of Pro-Vaccine Messages on Black Twitter. Health Communication 2023:1 View
  214. Wu X, Chen W, Zhang K, Lu Y. The dynamic impact of COVID-19 pandemic on park visits: A longitudinal study in the United States. Urban Forestry & Urban Greening 2023;90:128154 View
  215. Jerpan J, Moriceau V, Salis A, Klein R, Olivier F, Salles J. Changes in suicide-related tweets before and during the COVID-19 pandemic in France: The importance of social media monitoring in public health prediction. L'Encéphale 2023 View
  216. Kinanti T, Suyono S. Fenomena Speak Up pada Media Twitter (Study Deskriptif Korban Penipuan Melalui Gerakan “A Thread”). Jurnal Bisnis dan Komunikasi Digital 2023;1(1):12 View
  217. Lwin M, Yang S, Sheldenkar A, Yang X, Lee B. Assessing consumer rationality during a pandemic: Panic buying behaviours and its association with online social media discourse. Computers in Human Behavior Reports 2024;13:100361 View
  218. Ueda R, Han F, Zhang H, Aoki T, Ogasawara K. Verification in the Early Stages of the COVID-19 Pandemic: Sentiment Analysis of Japanese Twitter Users. JMIR Infodemiology 2024;4:e37881 View
  219. Kim D, Lim T, Hwang Y, Kim S. Predicting Support for COVID-19 Policies with Partisan Media Use and Negative Emotion: Evidence from the U.S. and South Korea. Journal of Health Communication 2023;28(sup2):32 View
  220. Wang X, Liu M, Luo F. Impact of the COVID-19 epidemic on collectivism and individualism in China: A study of Weibo users. Journal of Pacific Rim Psychology 2024;18 View
  221. Brassel S, Brunner M, Campbell A, Power E, Togher L. Exploring Discussions About Virtual Reality on Twitter to Inform Brain Injury Rehabilitation: Content and Network Analysis. Journal of Medical Internet Research 2024;26:e45168 View
  222. Haque A, Singh K, Kaphle S, Panchasara H, Tseng W. Shifting Workplace Paradigms: Twitter Sentiment Insights on Work from Home. Sustainability 2024;16(2):871 View
  223. Wang X, Vergeer M. Effect of Social Media Posts on Stock Market During COVID-19 Infodemic: An Agenda Diffusion Approach. SAGE Open 2024;14(1) View
  224. Lahav E, Shahrabani S, Rosenboim M, Tsutsui Y. The Effect of Being Vaccinated and National Vaccination Rates on Individuals’ Cognitions, Emotions, and Economic Expectations: Evidence from Israel. International Journal of Behavioral Medicine 2024 View
  225. Aldosery A, Carruthers R, Kay K, Cave C, Reynolds P, Kostkova P. Enhancing public health response: a framework for topics and sentiment analysis of COVID-19 in the UK using Twitter and the embedded topic model. Frontiers in Public Health 2024;12 View
  226. Charquero-Ballester M, Walter J, Rybner A, Nissen I, Enevoldsen K, Bechmann A, De Silva D. Emotions on Twitter as crisis imprint in high-trust societies: Do ambient affiliations affect emotional expression during the pandemic?. PLOS ONE 2024;19(3):e0296801 View
  227. Lwin M, Sheldenkar A, Tng P, Ovenseri-Ogbomo G. You must be myths-taken: Examining belief in falsehoods during the COVID-19 health crisis. PLOS ONE 2024;19(3):e0294471 View
  228. Hrbková L, Kudrnáč A. Fear, trust, and compliance with COVID-19 measures: a study of the mediating effect of trust in government on the relationship between fear and compliance. Journal of Public Policy 2024:1 View
  229. Li Y, Chen M, Lee H. Health communication on social media at the early stage of the pandemic: Examining health professionals’ COVID-19 related tweets. Social Science & Medicine 2024;347:116748 View
  230. Unlu A, Truong S, Sawhney N, Sivelä J, Tammi T. Tracing the dynamics of misinformation and vaccine stance in Finland amid COVID-19. Information, Communication & Society 2024:1 View
  231. Jain V, Kashyap K. Enhanced word vector space with ensemble deep learning model for COVID-19 Hindi text sentiment analysis. Multimedia Tools and Applications 2024 View
  232. Kabasawa K, Tsuda K. Proposal for a system to identify the causes and triggers of stress in infertility patients. Procedia Computer Science 2024;234:62 View
  233. Xu H, Muthya Sudheendra S, Huh J, Salecha A, Srivastava J. Influence of emotions on coping behaviors in crisis: a computational analysis of the COVID-19 outbreak. Journal of Computational Social Science 2024 View
  234. 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
  235. Shi S, Wang G, Zhang L. How to Respond? The Impact of Government Response on Emotions in Emergencies from the Perspective of Configuration. Systems 2024;12(6):183 View
  236. Breve B, Caruccio L, Cirillo S, Deufemia V, Polese G. Analyzing the worldwide perception of the Russia-Ukraine conflict through Twitter. Journal of Big Data 2024;11(1) View
  237. Stoica T, Andrews E, Deffner A, Griffith C, Grilli M, Andrews-Hanna J. Speaking Well and Feeling Good: Age-Related Differences in the Affective Language of Resting State Thought. Affective Science 2024 View

Books/Policy Documents

  1. Koinig I. Risk Management. View
  2. Wright K. Communicating Science in Times of Crisis. View
  3. Alsoubai A, Song J, Razi A, Dacre P, Wisniewski P. Social Computing and Social Media: Applications in Marketing, Learning, and Health. View
  4. Yan Y, Chin W, Leong C, Wang Y, Feng C. Mapping COVID-19 in Space and Time. View
  5. Babić K, Petrović M, Beliga S, Martinčić-Ipšić S, Jarynowski A, Meštrović A. Proceedings of Sixth International Congress on Information and Communication Technology. View
  6. 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
  7. Miliou I, Pavlopoulos J, Papapetrou P. Discovery Science. View
  8. Bogović P, Meštrović A, Martinčić-Ipšić S. Information and Software Technologies. View
  9. Rushee K, Rahim M, Levula A, Mahdavi M. Advanced Information Networking and Applications. View
  10. Zhao Q, Nie L, Xu X. Comparative Studies on Pandemic Control Policies and the Resilience of Society. View
  11. Koinig I. Advances in Advertising Research (Vol. XII). View
  12. Burns R. The Human Impact of the COVID-19 Pandemic. View
  13. Comito C. Artificial Intelligence in Healthcare and COVID-19. View
  14. Wang G, Li W, Wu S, Bai Q, Lai E. PRICAI 2023: Trends in Artificial Intelligence. View
  15. Seki Y. Advances in Sentiment Analysis - Techniques, Applications, and Challenges. View
  16. Shahi G. Digital Transformation. View
  17. Nadin M. Disrupt Science. View
  18. Osop H, Wong J, Lwin S, Lee C. Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration. View
  19. Flood F, Klausner M. Global Encyclopedia of Public Administration, Public Policy, and Governance. View
  20. Gyftopoulos S, Drosatos G, Pecchia L, Fico G, Kaldoudi E. MEDICON’23 and CMBEBIH’23. View
  21. Flood F, Klausner M. Global Encyclopedia of Public Administration, Public Policy, and Governance. View