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

Preprints (earlier versions) of this paper are available at, first published .
Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set

Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set

Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set

Authors of this article:

Emily Chen 1 Author Orcid Image ;   Kristina Lerman 1 Author Orcid Image ;   Emilio Ferrara 1 Author Orcid Image


  1. Abrams E, Greenhawt M. Mitigating Misinformation and Changing the Social Narrative. The Journal of Allergy and Clinical Immunology: In Practice 2020;8(10):3261 View
  2. Jiang J, Chen E, Yan S, Lerman K, Ferrara E. Political polarization drives online conversations about COVID ‐19 in the United States. Human Behavior and Emerging Technologies 2020;2(3):200 View
  3. Papakyriakopoulos O, Medina Serrano J, Hegelich S. The spread of COVID-19 conspiracy theories on social me-dia and the effect of content moderation. Harvard Kennedy School Misinformation Review 2020 View
  4. Stella M, Restocchi V, De Deyne S. #lockdown: Network-Enhanced Emotional Profiling in the Time of COVID-19. Big Data and Cognitive Computing 2020;4(2):14 View
  5. 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
  6. 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
  7. Jang H, Rempel E, Roth D, Carenini G, Janjua N. Tracking COVID-19 Discourse on Twitter in North America: Infodemiology Study Using Topic Modeling and Aspect-Based Sentiment Analysis. Journal of Medical Internet Research 2021;23(2):e25431 View
  8. Leis A, Ronzano F, Mayer M, Furlong L, Sanz F. Evaluating Behavioral and Linguistic Changes During Drug Treatment for Depression Using Tweets in Spanish: Pairwise Comparison Study. Journal of Medical Internet Research 2020;22(12):e20920 View
  9. 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
  10. 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
  11. Mutlu E, Oghaz T, Jasser J, Tutunculer E, Rajabi A, Tayebi A, Ozmen O, Garibay I. A stance data set on polarized conversations on Twitter about the efficacy of hydroxychloroquine as a treatment for COVID-19. Data in Brief 2020;33:106401 View
  12. Blázquez-Ochando M, Prieto-Gutiérrez J. Virus de ácido ribonucleico (ARN) y coronavirus en Google Dataset Search: alcance y correlación epidemiológica. El profesional de la información 2020 View
  13. Alnajashi H, Jabbad R, Lavorgna L. Behavioral practices of patients with multiple sclerosis during Covid-19 pandemic. PLOS ONE 2020;15(10):e0241103 View
  14. Battiston P, Kashyap R, Rotondi V. Reliance on scientists and experts during an epidemic: Evidence from the COVID-19 outbreak in Italy. SSM - Population Health 2021;13:100721 View
  15. Zheng H, Goh D, Lee C, Lee E, Theng Y. Uncovering temporal differences in COVID ‐19 tweets. Proceedings of the Association for Information Science and Technology 2020;57(1) View
  16. Ladeiras-Lopes R, Baciu L, Grapsa J, Sohaib A, Vidal-Perez R, Bohm A, Silvola H, Gimenez M, Muscoli S, Wallner M, Rakisheva A, Nagy V, Cowie M, Clarke S, Achenbach S. Social media in cardiovascular medicine: a contemporary review. European Heart Journal - Digital Health 2020;1(1):10 View
  17. Mourad A, Srour A, Harmanani H, Jenainati C, Arafeh M. Critical Impact of Social Networks Infodemic on Defeating Coronavirus COVID-19 Pandemic: Twitter-Based Study and Research Directions. IEEE Transactions on Network and Service Management 2020;17(4):2145 View
  18. Bracci A, Nadini M, Aliapoulios M, McCoy D, Gray I, Teytelboym A, Gallo A, Baronchelli A. Dark Web Marketplaces and COVID-19: before the vaccine. EPJ Data Science 2021;10(1) View
  19. 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
  20. Bracci A, Nadini M, Aliapoulios M, McCoy D, Gray I, Teytelboym A, Gallo A, Baronchelli A. The COVID-19 Online Shadow Economy. SSRN Electronic Journal 2020 View
  21. 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
  22. Lamsal R. Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence 2020 View
  23. 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
  24. Kaur S, Kaul P, Zadeh P. Monitoring the Dynamics of Emotions during COVID-19 Using Twitter Data. Procedia Computer Science 2020;177:423 View
  25. Ho H, Chen Y, Yen C. Different impacts of COVID-19-related information sources on public worry: An online survey through social media. Internet Interventions 2020;22:100350 View
  26. Gencoglu O. Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19. Machine Learning and Knowledge Extraction 2020;2(4):603 View
  27. Ferrara E, Cresci S, Luceri L. Misinformation, manipulation, and abuse on social media in the era of COVID-19. Journal of Computational Social Science 2020;3(2):271 View
  28. Petersen K, Gerken J. #Covid-19: An exploratory investigation of hashtag usage on Twitter. Health Policy 2021;125(4):541 View
  29. 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
  30. 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
  31. Tan T, Huang T, Wang X, Zuo Z. A preliminary investigation of COVID ‐19 transmission in the United States by incorporating social media sentiments. Proceedings of the Association for Information Science and Technology 2020;57(1) View
  32. Nikolovska M, Johnson S, Ekblom P. “Show this thread”: policing, disruption and mobilisation through Twitter. An analysis of UK law enforcement tweeting practices during the Covid-19 pandemic. Crime Science 2020;9(1) View
  33. Kearney M, Chiang S, Massey P. The Twitter origins and evolution of the COVID-19 “plandemic” conspiracy theory. Harvard Kennedy School Misinformation Review 2020 View
  34. Alshaabi T, Arnold M, Minot J, Adams J, Dewhurst D, Reagan A, Muhamad R, Danforth C, Dodds P, Rocha L. How the world’s collective attention is being paid to a pandemic: COVID-19 related n-gram time series for 24 languages on Twitter. PLOS ONE 2021;16(1):e0244476 View
  35. NUDI R, CAMPAGNA M, PARMA A, NUDI A, BIONDI ZOCCAI G. Breakthrough healthcare technologies in the COVID-19 era: a unique opportunity for cardiovascular practitioners and patients. Panminerva Medica 2021;63(1) View
  36. Al-Ramahi M, Elnoshokaty A, El-Gayar O, Nasralah T, Wahbeh A. Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data. JMIR Public Health and Surveillance 2021;7(4):e26780 View
  37. Cotfas L, Delcea C, Roxin I, Ioanas C, Gherai D, Tajariol F. The Longest Month: Analyzing COVID-19 Vaccination Opinions Dynamics From Tweets in the Month Following the First Vaccine Announcement. IEEE Access 2021;9:33203 View
  38. Chen E, Chang H, Rao A, Lerman K, Cowan G, Ferrara E. COVID-19 misinformation and the 2020 U.S. presidential election. Harvard Kennedy School Misinformation Review 2021 View
  39. Kim H, Saffer A, Liu W, Sun J, Li Y, Zhen L, Yang A. How Public Health Agencies Break through COVID-19 Conversations: A Strategic Network Approach to Public Engagement. Health Communication 2021:1 View
  40. Chen N, Zhang Y, Du W, Li Y, Chen M, Zheng X. KE-CNN: A new social sensing method for extracting geographical attributes from text semantic features and its application in Wuhan, China. Computers, Environment and Urban Systems 2021;88:101629 View
  41. Gerts D, Shelley C, Parikh N, Pitts T, Watson Ross C, Fairchild G, Vaquera Chavez N, Daughton A. “Thought I’d Share First” and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study. JMIR Public Health and Surveillance 2021;7(4):e26527 View
  42. Lash M, Sajeesh S, Araz O. Predicting Retail Mobility during the COVID-19 Pandemic. SSRN Electronic Journal 2021 View
  43. Pulido-Polo M, Hernández-Santaolalla V, Lozano-González A. Uso institucional de Twitter para combatir la infodemia causada por la crisis sanitaria de la Covid-19. El profesional de la información 2021 View
  44. Zhou Q, Zhang C. Breaking community boundary: Comparing academic and social communication preferences regarding global pandemics. Journal of Informetrics 2021;15(3):101162 View
  45. 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
  46. Liu P. COVID-19 information on social media and preventive behaviors: Managing the pandemic through personal responsibility. Social Science & Medicine 2021;277:113928 View
  47. Chen H, Zhu Z, Qi F, Ye Y, Liu Z, Sun M, Jin J. Country Image in COVID-19 Pandemic: A Case Study of China. IEEE Transactions on Big Data 2021;7(1):81 View
  48. Park S, Han S, Kim J, Molaie M, Vu H, Singh K, Han J, Lee W, Cha M. COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication. Journal of Medical Internet Research 2021;23(3):e23272 View
  49. Song X, Petrak J, Jiang Y, Singh I, Maynard D, Bontcheva K, Martinčić-Ipšić S. Classification aware neural topic model for COVID-19 disinformation categorisation. PLOS ONE 2021;16(2):e0247086 View
  50. Ahmed U, Mukhiya S, Srivastava G, Lamo Y, Lin J. Attention-Based Deep Entropy Active Learning Using Lexical Algorithm for Mental Health Treatment. Frontiers in Psychology 2021;12 View
  51. Torres A, Kelley C, Kelley S, Piña G, Garcia-Baza I, Griffith I. An Analysis of Digital Media Data to Understand Parents’ Concerns During the COVID-19 Pandemic to Enhance Effective Science Communication. Journal of Creative Communications 2021;16(2):168 View
  52. Li Z, Wang X. Research on Sentiment Analysis Model Due to COVID-19 Using Social Media. Journal of Physics: Conference Series 2021;1856(1):012064 View
  53. Chaves-Montero A, Relinque-Medina F, Fernández-Borrero M, Vázquez-Aguado O. Twitter, Social Services and Covid-19: Analysis of Interactions between Political Parties and Citizens. Sustainability 2021;13(4):2187 View
  54. Rao A, Morstatter F, Hu M, Chen E, Burghardt K, Ferrara E, Lerman K. Political Partisanship and Antiscience Attitudes in Online Discussions About COVID-19: Twitter Content Analysis. Journal of Medical Internet Research 2021;23(6):e26692 View
  55. Rivieccio B, Micheletti A, Maffeo M, Zignani M, Comunian A, Nicolussi F, Salini S, Manzi G, Auxilia F, Giudici M, Naldi G, Gaito S, Castaldi S, Biganzoli E, Guidi B. CoViD-19, learning from the past: A wavelet and cross-correlation analysis of the epidemic dynamics looking to emergency calls and Twitter trends in Italian Lombardy region. PLOS ONE 2021;16(2):e0247854 View
  56. Probierz E, Galuszka A, Dzida T. Twitter Text Data from #Covid-19: Analysis of Changes in Time Using Exploratory Sentiment Analysis. Journal of Physics: Conference Series 2021;1828(1):012138 View
  57. 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 View
  58. Padilha R, Theóphilo A, Andaló F, Vega-Oliveros D, Cardenuto J, Bertocco G, Nascimento J, Yang J, Rocha A. A Inteligência Artificial e os desafios da Ciência Forense Digital no século XXI. Estudos Avançados 2021;35(101):113 View
  59. Martínez Beltrán E, Quiles Pérez M, Pastor-Galindo J, Nespoli P, García Clemente F, Gómez Mármol F. COnVIDa: COVID-19 multidisciplinary data collection and dashboard. Journal of Biomedical Informatics 2021;117:103760 View
  60. Roy S, Ghosh P. A Comparative Study on Distancing, Mask and Vaccine Adoption Rates from Global Twitter Trends. Healthcare 2021;9(5):488 View
  61. González L, Devís-Devís J, Pellicer-Chenoll M, Pans M, Pardo-Ibañez A, García-Massó X, Peset F, Garzón-Farinós F, Pérez-Samaniego V. The Impact of COVID-19 on Sport in Twitter: A Quantitative and Qualitative Content Analysis. International Journal of Environmental Research and Public Health 2021;18(9):4554 View
  62. Zdonek D, Król K. The Impact of Sex and Personality Traits on Social Media Use during the COVID-19 Pandemic in Poland. Sustainability 2021;13(9):4793 View
  63. Li Y, Shin J, Sun J, Kim H, Qu Y, Yang A. Organizational sensemaking in tough times: The ecology of NGOs’ COVID-19 issue discourse communities on social media. Computers in Human Behavior 2021;122:106838 View
  64. Andreadis S, Antzoulatos G, Mavropoulos T, Giannakeris P, Tzionis G, Pantelidis N, Ioannidis K, Karakostas A, Gialampoukidis I, Vrochidis S, Kompatsiaris I. A social media analytics platform visualising the spread of COVID-19 in Italy via exploitation of automatically geotagged tweets. Online Social Networks and Media 2021;23:100134 View
  65. Cheng Y, Zhang J, Wei W, Zhao B. Effects of urban parks on residents’ expressed happiness before and during the COVID-19 pandemic. Landscape and Urban Planning 2021;212:104118 View
  66. Feinberg I, Owen-Smith A, O'Connor M, Ogrodnick M, Rothenberg R, Eriksen M. Strengthening Culturally Competent Health Communication. Health Security 2021;19(S1):S-41 View
  67. La Bella E, Allen C, Lirussi F. Communication vs evidence: What hinders the outreach of science during an infodemic? A narrative review. Integrative Medicine Research 2021;10(4):100731 View
  68. Grande D, Mitra N, Marti X, Merchant R, Asch D, Dolan A, Sharma M, Cannuscio C. Consumer Views on Using Digital Data for COVID-19 Control in the United States. JAMA Network Open 2021;4(5):e2110918 View
  69. Selman L, Chamberlain C, Sowden R, Chao D, Selman D, Taubert M, Braude P. Sadness, despair and anger when a patient dies alone from COVID-19: A thematic content analysis of Twitter data from bereaved family members and friends. Palliative Medicine 2021;35(7):1267 View
  70. Daughton A, Shelley C, Barnard M, Gerts D, Watson Ross C, Crooker I, Nadiga G, Mukundan N, Vaquera Chavez N, Parikh N, Pitts T, Fairchild G. Mining and Validating Social Media Data for COVID-19–Related Human Behaviors Between January and July 2020: Infodemiology Study. Journal of Medical Internet Research 2021;23(5):e27059 View
  71. Cheng M, Wang S, Yan X, Yang T, Wang W, Huang Z, Xiao X, Nazarian S, Bogdan P. A COVID-19 Rumor Dataset. Frontiers in Psychology 2021;12 View
  72. Kydros D, Argyropoulou M, Vrana V. A Content and Sentiment Analysis of Greek Tweets during the Pandemic. Sustainability 2021;13(11):6150 View
  73. Choli M, Kuss D. Perceptions of blame on social media during the coronavirus pandemic. Computers in Human Behavior 2021;124:106895 View
  74. 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
  75. 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 2021;ahead-of-print(ahead-of-print) View
  76. Bowden-Green T, Hinds J, Joinson A. Personality and Motives for Social Media Use When Physically Distanced: A Uses and Gratifications Approach. Frontiers in Psychology 2021;12 View
  77. Melotte S, Kejriwal M. A Geo-Tagged COVID-19 Twitter Dataset for 10 North American Metropolitan Areas over a 255-Day Period. Data 2021;6(6):64 View
  78. Balasubramaniam T, Nayak R, Luong K, Bashar M. Identifying Covid-19 misinformation tweets and learning their spatio-temporal topic dynamics using Nonnegative Coupled Matrix Tensor Factorization. Social Network Analysis and Mining 2021;11(1) View
  79. Amit A, Pepito V, Gutierrez B, Rawson T. Data Sharing in Southeast Asia During the First Wave of the COVID-19 Pandemic. Frontiers in Public Health 2021;9 View
  80. Flasiński K. Media Narrative Regarding Restrictions on Social Life During the COVID-19 Pandemic on Zeszyty Prasoznawcze 2021;64(2 (246)):101 View
  81. Yang C, Zhou X, Zafarani R. CHECKED: Chinese COVID-19 fake news dataset. Social Network Analysis and Mining 2021;11(1) View
  82. Gallagher R, Doroshenko L, Shugars S, Lazer D, Foucault Welles B. Sustained Online Amplification of COVID-19 Elites in the United States. Social Media + Society 2021;7(2):205630512110249 View
  83. Singh G, Rego J, Chambers S, Fox J. Health Professionals’ Perspectives of the Role of Palliative Care During COVID-19: Content Analysis of Articles and Blogs Posted on Twitter. American Journal of Hospice and Palliative Medicine® 2021:104990912110242 View
  84. Dogan O, Tiwari S, Jabbar M, Guggari S. A systematic review on AI/ML approaches against COVID-19 outbreak. Complex & Intelligent Systems 2021 View
  85. Caldarelli G, De Nicola R, Petrocchi M, Pratelli M, Saracco F. Flow of online misinformation during the peak of the COVID-19 pandemic in Italy. EPJ Data Science 2021;10(1) View
  86. 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
  87. Bathina K, ten Thij M, Valdez D, Rutter L, Bollen J, Osório F. Declining well-being during the COVID-19 pandemic reveals US social inequities. PLOS ONE 2021;16(7):e0254114 View
  88. Wahid J, Shi L, Gao Y, Yang B, Tao Y, Wei L, Hussain S. Identifying and Characterizing the Propagation Scale of COVID-19 Situational Information on Twitter: A Hybrid Text Analytic Approach. Applied Sciences 2021;11(14):6526 View
  89. 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
  90. Aiello L, Quercia D, Zhou K, Constantinides M, Šćepanović S, Joglekar S. How epidemic psychology works on Twitter: evolution of responses to the COVID-19 pandemic in the U.S.. Humanities and Social Sciences Communications 2021;8(1) View

Books/Policy Documents

  1. Zheng H, Goh D, Lee E, Lee C, Theng Y. Digital Libraries at Times of Massive Societal Transition. View
  2. Shah C, Sebastian M. Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation. View
  3. Inuwa-Dutse I. Data Science Advancements in Pandemic and Outbreak Management. View
  4. Kydros D, Argyropoulou M, Vrana V. Strategic Innovative Marketing and Tourism in the COVID-19 Era. View
  5. Wright K. Communicating Science in Times of Crisis. View
  6. Li B, Chen Z, Lim S. Geographical Information Systems Theory, Applications and Management. View
  7. Uddin M, Shorif S, Sarker A. Vision, Sensing and Analytics: Integrative Approaches. View
  8. Alexiou E, Antonakakis A, Jevtic N, Sideras G, Farmaki E, Foutsitzi S, Kermanidis K. Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops. View
  9. Tan H, Lee C, Goh D, Zheng H, Theng Y. HCI International 2021 - Posters. View