Published on in Vol 6 , No 4 (2020) :Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21978, first published .
Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study

Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study

Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study

Authors of this article:

Sakun Boon-Itt 1 Author Orcid Image ;   Yukolpat Skunkan 2 Author Orcid Image

Journals

  1. 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
  2. Sansone A, Cignarelli A, Mollaioli D, Ciocca G, Limoncin E, Romanelli F, Balercia G, Jannini E. The Social Aspects of Sexual Health: A Twitter-Based Analysis of Valentine’s Day Perception. Sexes 2021;2(1):50 View
  3. Zhang S, Pian W, Ma F, Ni Z, Liu Y. Characterizing the COVID-19 Infodemic on Chinese Social Media: Exploratory Study. JMIR Public Health and Surveillance 2021;7(2):e26090 View
  4. Gao Y, Xie Z, Li D. Electronic Cigarette Users' Perspective on the COVID-19 Pandemic: Observational Study Using Twitter Data. JMIR Public Health and Surveillance 2021;7(1):e24859 View
  5. 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
  6. 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
  7. Sooknanan J, Mays N. Harnessing Social Media in the Modelling of Pandemics—Challenges and Opportunities. Bulletin of Mathematical Biology 2021;83(5) View
  8. 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
  9. Ghasiya P, Okamura K. Investigating COVID-19 News Across Four Nations: A Topic Modeling and Sentiment Analysis Approach. IEEE Access 2021;9:36645 View
  10. Bhatnagar S, Choubey N. Making sense of tweets using sentiment analysis on closely related topics. Social Network Analysis and Mining 2021;11(1) View
  11. Adikari A, Nawaratne R, De Silva D, Ranasinghe S, Alahakoon O, Alahakoon D. Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence. Journal of Medical Internet Research 2021;23(4):e27341 View
  12. Satu M, Khan M, Mahmud M, Uddin S, Summers M, Quinn J, Moni M. TClustVID: A novel machine learning classification model to investigate topics and sentiment in COVID-19 tweets. Knowledge-Based Systems 2021;226:107126 View
  13. Batra R, Imran A, Kastrati Z, Ghafoor A, Daudpota S, Shaikh S. Evaluating Polarity Trend Amidst the Coronavirus Crisis in Peoples’ Attitudes toward the Vaccination Drive. Sustainability 2021;13(10):5344 View
  14. 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
  15. Kydros D, Argyropoulou M, Vrana V. A Content and Sentiment Analysis of Greek Tweets during the Pandemic. Sustainability 2021;13(11):6150 View
  16. Tsai M, Wang Y. Analyzing Twitter Data to Evaluate People’s Attitudes towards Public Health Policies and Events in the Era of COVID-19. International Journal of Environmental Research and Public Health 2021;18(12):6272 View
  17. ONAN A. COVID-19 ile İlgili Sosyal Medya Gönderilerinin Metin Madenciliği Yöntemlerine Dayalı Olarak Zaman-Mekansal Analizi. European Journal of Science and Technology 2021 View
  18. Ersoy M, Dambo T. Covering the Covid-19 Pandemic Using Peace Journalism Approach. Journalism Practice 2023;17(4):841 View
  19. Xiong Z, Li P, Lyu H, Luo J. Social Media Opinions on Working From Home in the United States During the COVID-19 Pandemic: Observational Study. JMIR Medical Informatics 2021;9(7):e29195 View
  20. A. Rahim A, Ibrahim M, Musa K, Chua S. Facebook Reviews as a Supplemental Tool for Hospital Patient Satisfaction and Its Relationship with Hospital Accreditation in Malaysia. International Journal of Environmental Research and Public Health 2021;18(14):7454 View
  21. Margus C, Brown N, Hertelendy A, Safferman M, Hart A, Ciottone G. Emergency Physician Twitter Use in the COVID-19 Pandemic as a Potential Predictor of Impending Surge: Retrospective Observational Study. Journal of Medical Internet Research 2021;23(7):e28615 View
  22. Luo C, Ji K, Tang Y, Du Z. Exploring the Expression Differences Between Professionals and Laypeople Toward the COVID-19 Vaccine: Text Mining Approach. Journal of Medical Internet Research 2021;23(8):e30715 View
  23. Azizi F, Hajiabadi H, Vahdat-Nejad H, Khosravi M. Detecting and analyzing topics of massive COVID-19 related tweets for various countries. Computers and Electrical Engineering 2023;106:108561 View
  24. Feng Y, Shah C. Unifying telescope and microscope: A multi-lens framework with open data for modeling emerging events. Information Processing & Management 2022;59(2):102811 View
  25. Yoo M, Jang C. Physical rehabilitation on social media during COVID-19: Topics and sentiments analysis of tweets. Annals of Physical and Rehabilitation Medicine 2022;65(1):101589 View
  26. 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
  27. 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
  28. Lim S, Ng Q, Xin X, Lim Y, Boon E, Liew T. Public Discourse Surrounding Suicide during the COVID-19 Pandemic: An Unsupervised Machine Learning Analysis of Twitter Posts over a One-Year Period. International Journal of Environmental Research and Public Health 2022;19(21):13834 View
  29. 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
  30. Waheeb S, Khan N, Shang X. Topic Modeling and Sentiment Analysis of Online Education in the COVID-19 Era Using Social Networks Based Datasets. Electronics 2022;11(5):715 View
  31. Bizzotto N, Morlino S, Schulz P. Misinformation in Italian Online Mental Health Communities During the COVID-19 Pandemic: Protocol for a Content Analysis Study. JMIR Research Protocols 2022;11(5):e35347 View
  32. Quach H, Pham T, Hoang N, Phung D, Nguyen V, Le S, Le T, Bui T, Le D, Dang A, Tran D, Ngu N, Vogt F, Nguyen C, Sung W. Using ‘infodemics’ to understand public awareness and perception of SARS-CoV-2: A longitudinal analysis of online information about COVID-19 incidence and mortality during a major outbreak in Vietnam, July—September 2020. PLOS ONE 2022;17(4):e0266299 View
  33. Tokac U, Brysiewicz P, Chipps J. Public perceptions on Twitter of nurses during the COVID-19 pandemic. Contemporary Nurse 2022;58(5-6):414 View
  34. Athanasiou M, Fragkozidis G, Zarkogianni K, Nikita K. Long Short-term Memory–Based Prediction of the Spread of Influenza-Like Illness Leveraging Surveillance, Weather, and Twitter Data: Model Development and Validation. Journal of Medical Internet Research 2023;25:e42519 View
  35. Huang X, Wang S, Zhang M, Hu T, Hohl A, She B, Gong X, Li J, Liu X, Gruebner O, Liu R, Li X, Liu Z, Ye X, Li Z. Social media mining under the COVID-19 context: Progress, challenges, and opportunities. International Journal of Applied Earth Observation and Geoinformation 2022;113:102967 View
  36. Zheng Z, Xie Z, Li D. Discussion of waterpipe tobacco smoking on reddit. Heliyon 2022;8(9):e10635 View
  37. Zhang Q, Shi Y, English A. COVID-19 Vaccine Uptake in the Context of the First Delta Outbreak in China During the Early Summer of 2021: The Role of Geographical Distance and Vaccine Talk. Risk Management and Healthcare Policy 2022;Volume 15:1203 View
  38. Scarpino I, Zucco C, Vallelunga R, Luzza F, Cannataro M. Investigating Topic Modeling Techniques to Extract Meaningful Insights in Italian Long COVID Narration. BioTech 2022;11(3):41 View
  39. Dong L, Yang L. COVID-19 anxiety: The impact of older adults’ transmission of negative information and online social networks. Aging and Health Research 2023;3(1):100119 View
  40. 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
  41. Rahim A, Ibrahim M, Musa K, Chua S, Yaacob N. Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and Facebook. Healthcare 2021;9(10):1369 View
  42. Delcea C, Cotfas L, Crăciun L, Molănescu A. New Wave of COVID-19 Vaccine Opinions in the Month the 3rd Booster Dose Arrived. Vaccines 2022;10(6):881 View
  43. Melissa M, Jillian J, Jennifer E, Daniel G, Andrew P. Review and thematic analysis of guiding principles for effective crisis communication using social media. Journal of Public Health and Epidemiology 2022;14(2):72 View
  44. Mittal R, Mittal A, Aggarwal I. Identification of affective valence of Twitter generated sentiments during the COVID-19 outbreak. Social Network Analysis and Mining 2021;11(1) View
  45. Jones R, Mougouei D, Evans S. Understanding the emotional response to COVID‐19 information in news and social media: A mental health perspective. Human Behavior and Emerging Technologies 2021;3(5):832 View
  46. Binkheder S, Aldekhyyel R, AlMogbel A, Al-Twairesh N, Alhumaid N, Aldekhyyel S, Jamal A. Public Perceptions around mHealth Applications during COVID-19 Pandemic: A Network and Sentiment Analysis of Tweets in Saudi Arabia. International Journal of Environmental Research and Public Health 2021;18(24):13388 View
  47. Grabar N, Grouin C. Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing. Yearbook of Medical Informatics 2021;30(01):257 View
  48. 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
  49. Chen M, Du W. The predicting public sentiment evolution on public emergencies under deep learning and internet of things. The Journal of Supercomputing 2023;79(6):6452 View
  50. Yoo P, Movahed M, Rue I, Santos C, Majnemer A, Shikako K. Changes in Use of a Leisure Activity Mobile App for Children With Disabilities During the COVID-19 Pandemic: Retrospective Study. JMIR Pediatrics and Parenting 2022;5(1):e32274 View
  51. 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
  52. Kwon N, Oh J, Ha E. Topic and Trends of Public Perception and Sentiments of COVID-19 Pandemic in South Korea: A Text Mining Approach. The Ewha Medical Journal 2022;45(2):46 View
  53. Huang S, Tsao S, Chen H, Bin Noon G, Li L, Yang Y, Butt Z. Topic Modelling and Sentiment Analysis of Tweets Related to Freedom Convoy 2022 in Canada. International Journal of Public Health 2022;67 View
  54. Ye Z, Li R, Wu J. Dynamic Demand Evaluation of COVID-19 Medical Facilities in Wuhan Based on Public Sentiment. International Journal of Environmental Research and Public Health 2022;19(12):7045 View
  55. Nia Z, Asgary A, Bragazzi N, Mellado B, Orbinski J, Wu J, Kong J. Nowcasting unemployment rate during the COVID-19 pandemic using Twitter data: The case of South Africa. Frontiers in Public Health 2022;10 View
  56. Park J, Mistur E, Kim D, Mo Y, Hoefer R. Toward human-centric urban infrastructure: Text mining for social media data to identify the public perception of COVID-19 policy in transportation hubs. Sustainable Cities and Society 2022;76:103524 View
  57. Baird A, Xia Y, Cheng Y. Consumer perceptions of telehealth for mental health or substance abuse: a Twitter-based topic modeling analysis. JAMIA Open 2022;5(2) View
  58. Ntompras C, Drosatos G, Kaldoudi E. A high-resolution temporal and geospatial content analysis of Twitter posts related to the COVID-19 pandemic. Journal of Computational Social Science 2022;5(1):687 View
  59. K. Sufi F, Alsulami M. AI-based Automated Extraction of Location-Oriented COVID-19 Sentiments. Computers, Materials & Continua 2022;72(2):3631 View
  60. Tseng W, Lin P, Wu P, Kao C. Examining patient flow in a tertiary hospital’s emergency department at a low coronavirus prevalence region. BMC Emergency Medicine 2022;22(1) View
  61. Guidry J, O’Donnell N, Meganck S, Lovari A, Miller C, Messner M, Hill A, Medina-Messner V, Carlyle K. Tweeting a Pandemic: Communicating #COVID19 Across the Globe. Health Communication 2022:1 View
  62. Qiao S, Li Z, Liang C, Li X, Rudisill C. Three dimensions of COVID‐19 risk perceptions and their socioeconomic correlates in the United States: A social media analysis. Risk Analysis 2022 View
  63. Guber D. Research Synthesis. Public Opinion Quarterly 2022;85(4):1103 View
  64. Chin H, Lima G, Shin M, Zhunis A, Cha C, Choi J, Cha M. User-Chatbot Conversations During the COVID-19 Pandemic: Study Based on Topic Modeling and Sentiment Analysis. Journal of Medical Internet Research 2023;25:e40922 View
  65. Sittar A, Major D, Mello C, Mladenic D, Grobelnik M. Political and Economic Patterns in COVID-19 News: From Lockdown to Vaccination. IEEE Access 2022;10:40036 View
  66. Kim M, Noh Y, Yamada A, Hong S. Comparison of the Erectile Dysfunction Drugs Sildenafil and Tadalafil Using Patient Medication Reviews: Topic Modeling Study. JMIR Medical Informatics 2022;10(2):e32689 View
  67. Wang H, Sun K, Wang Y. Exploring the Chinese Public’s Perception of Omicron Variants on Social Media: LDA-Based Topic Modeling and Sentiment Analysis. International Journal of Environmental Research and Public Health 2022;19(14):8377 View
  68. Kandasamy V, Trojovský P, Machot F, Kyamakya K, Bacanin N, Askar S, Abouhawwash M. Sentimental Analysis of COVID-19 Related Messages in Social Networks by Involving an N-Gram Stacked Autoencoder Integrated in an Ensemble Learning Scheme. Sensors 2021;21(22):7582 View
  69. Khalid A, Warraich N, Ali I. Digital information channels during the COVID-19 global health emergency through a situational awareness lens: a study of Pakistani citizens. Global Knowledge, Memory and Communication 2023 View
  70. Fakieh B, S. AL-Malaise AL-Ghamdi A, Saleem F, Ragab M. Optimal Machine Learning Driven Sentiment Analysis on COVID-19 Twitter Data. Computers, Materials & Continua 2023;75(1):81 View
  71. Dsouza V, Rajkhowa P, Mallya B, Raksha D, Mrinalini V, Cauvery K, Raj R, Toby I, Pattanshetty S, Brand H. A sentiment and content analysis of tweets on monkeypox stigma among the LGBTQ+ community: A cue to risk communication plan. Dialogues in Health 2023;2:100095 View
  72. Ginossar T, Cruickshank I, Zheleva E, Sulskis J, Berger-Wolf T. Cross-platform spread: vaccine-related content, sources, and conspiracy theories in YouTube videos shared in early Twitter COVID-19 conversations. Human Vaccines & Immunotherapeutics 2022;18(1):1 View
  73. 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
  74. 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
  75. Vanam H, JebersonRetna Raj R, Janga V. Novel cluster set optimization model with unique identifier tagging for twitter data analysis. Journal of Intelligent & Fuzzy Systems 2023;44(2):2031 View
  76. Weng Z, Lin A. Public Opinion Manipulation on Social Media: Social Network Analysis of Twitter Bots during the COVID-19 Pandemic. International Journal of Environmental Research and Public Health 2022;19(24):16376 View
  77. McMillan K, Anderson K, Christley R. Pooches on a platform: Text mining twitter for sector perceptions of dogs during a global pandemic. Frontiers in Veterinary Science 2023;10 View
  78. ÖZYURT Ö, KISA N. COVID-19 Salgını Sürecinde Uzaktan Eğitime İlişkin Tweetlerin Duygusal Analizi. Journal of Computer and Education Research 2021;9(18):853 View
  79. 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
  80. Kant G, Wiebelt L, Weisser C, Kis-Katos K, Luber M, Säfken B. An iterative topic model filtering framework for short and noisy user-generated data: analyzing conspiracy theories on twitter. International Journal of Data Science and Analytics 2022 View
  81. Alkhaldi N, Asiri Y, Mashraqi A, Halawani H, Abdel-Khalek S, Mansour R. Leveraging Tweets for Artificial Intelligence Driven Sentiment Analysis on the COVID-19 Pandemic. Healthcare 2022;10(5):910 View
  82. Alanazi S. Robust Sentimental Class Prediction Based on Cryptocurrency-Related Tweets Using Tetrad of Feature Selection Techniques in Combination with Filtered Classifier. Applied Sciences 2022;12(12):6070 View
  83. Kobayashi R, Takedomi Y, Nakayama Y, Suda T, Uno T, Hashimoto T, Toyoda M, Yoshinaga N, Kitsuregawa M, Rocha L. Evolution of Public Opinion on COVID-19 Vaccination in Japan: Large-Scale Twitter Data Analysis. Journal of Medical Internet Research 2022;24(12):e41928 View
  84. Ljajić A, Prodanović N, Medvecki D, Bašaragin B, Mitrović J. Uncovering the Reasons Behind COVID-19 Vaccine Hesitancy in Serbia: Sentiment-Based Topic Modeling. Journal of Medical Internet Research 2022;24(11):e42261 View
  85. Sufi F, Alsulami M, Gutub A. Automating Global Threat-Maps Generation via Advancements of News Sensors and AI. Arabian Journal for Science and Engineering 2023;48(2):2455 View
  86. 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
  87. Schmälzle R, Wilcox S. Harnessing Artificial Intelligence for Health Message Generation: The Folic Acid Message Engine. Journal of Medical Internet Research 2022;24(1):e28858 View
  88. Lin J, Chien T, Yeh Y, Ho S, Chou W. Using sentiment analysis to identify similarities and differences in research topics and medical subject headings (MeSH terms) between Medicine (Baltimore) and the Journal of the Formosan Medical Association (JFMA) in 2020. Medicine 2022;101(11) View
  89. Bogdanowicz A, Guan C, Sasahara K. Dynamic topic modeling of twitter data during the COVID-19 pandemic. PLOS ONE 2022;17(5):e0268669 View
  90. 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 2022 View
  91. Rahmanti A, Chien C, Nursetyo A, Husnayain A, Wiratama B, Fuad A, Yang H, Li Y. Social media sentiment analysis to monitor the performance of vaccination coverage during the early phase of the national COVID-19 vaccine rollout. Computer Methods and Programs in Biomedicine 2022;221:106838 View
  92. Hu M, Conway M. Perspectives of the COVID-19 Pandemic on Reddit: Comparative Natural Language Processing Study of the United States, the United Kingdom, Canada, and Australia. JMIR Infodemiology 2022;2(2):e36941 View
  93. Michailidis P. Visualizing Social Media Research in the Age of COVID-19. Information 2022;13(8):372 View
  94. Oliveira F, Haque A, Mougouei D, Evans S, Sichman J, Singh M. Investigating the Emotional Response to COVID-19 News on Twitter: A Topic Modeling and Emotion Classification Approach. IEEE Access 2022;10:16883 View
  95. Wu J, Wang L, Hua Y, Li M, Zhou L, Bates D, Yang J. Trend and Co-occurrence Network of COVID-19 Symptoms From Large-Scale Social Media Data: Infoveillance Study. Journal of Medical Internet Research 2023;25:e45419 View
  96. Mozes M, van der Vegt I, Kleinberg B. A repeated-measures study on emotional responses after a year in the pandemic. Scientific Reports 2021;11(1) View
  97. Sitaula C, Basnet A, Mainali A, Shahi T, G T. Deep Learning-Based Methods for Sentiment Analysis on Nepali COVID-19-Related Tweets. Computational Intelligence and Neuroscience 2021;2021:1 View
  98. 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
  99. Kwon S, Park A. Understanding user responses to the COVID-19 pandemic on Twitter from a terror management theory perspective: Cultural differences among the US, UK and India. Computers in Human Behavior 2022;128:107087 View
  100. Ding Q, Massey D, Huang C, Grady C, Lu Y, Cohen A, Matzner P, Mahajan S, Caraballo C, Kumar N, Xue Y, Dreyer R, Roy B, Krumholz H. Tracking Self-reported Symptoms and Medical Conditions on Social Media During the COVID-19 Pandemic: Infodemiological Study. JMIR Public Health and Surveillance 2021;7(9):e29413 View
  101. Santoveña-Casal S, Gil-Quintana J, Ramos L. Digital citizens’ feelings in national #Covid 19 campaigns in Spain. Heliyon 2021;7(10):e08112 View
  102. 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
  103. Weger R, Lossio-Ventura J, Rose-McCandlish M, Shaw J, Sinclair S, Pereira F, Chung J, Atlas L. Trends in Language Use During the COVID-19 Pandemic and Relationship Between Language Use and Mental Health: Text Analysis Based on Free Responses From a Longitudinal Study. JMIR Mental Health 2023;10:e40899 View
  104. Tan Z, Datta A. The first year of the Covid-19 pandemic through the lens of r/Coronavirus subreddit: an exploratory study. Health and Technology 2023;13(2):301 View
  105. AL-Ahdal T, Coker D, Awad H, Reda A, Żuratyński P, Khailaie S. Improving Public Health Policy by Comparing the Public Response during the Start of COVID-19 and Monkeypox on Twitter in Germany: A Mixed Methods Study. Vaccines 2022;10(12):1985 View
  106. Aleksandric A, Anderson H, Melcher S, Nilizadeh S, Wilson G. Spanish Facebook Posts as an Indicator of COVID-19 Vaccine Hesitancy in Texas. Vaccines 2022;10(10):1713 View
  107. Khalil M, Belokrys G. What Does Twitter Say About Self-Regulated Learning? Mapping Tweets From 2011 to 2021. Frontiers in Psychology 2022;13 View
  108. Lepelaar M, Wahby A, Rossouw M, Nikitin L, Tibble K, Ryan P, Watson R. Sentiment Analysis of Social Survey Data for Local City Councils. Journal of Sensor and Actuator Networks 2022;11(1):7 View
  109. Ismail H, Serhani M, Hussien N, Elabyad R, Navaz A. Public wellbeing analytics framework using social media chatter data. Social Network Analysis and Mining 2022;12(1) View
  110. Wang Y, Zhong C, Gao Q, Cabrera-Arnau C. Understanding internal migration in the UK before and during the COVID-19 pandemic using twitter data. Urban Informatics 2022;1(1) View
  111. Shahi T, Sitaula C, Paudel N, G T. A Hybrid Feature Extraction Method for Nepali COVID-19-Related Tweets Classification. Computational Intelligence and Neuroscience 2022;2022:1 View
  112. Das R, Ahmed W. Rethinking Fake News: Disinformation and Ideology during the time of COVID-19 Global Pandemic. IIM Kozhikode Society & Management Review 2022;11(1):146 View
  113. Zhang T, Yu L. The Relationship between Government Information Supply and Public Information Demand in the Early Stage of COVID-19 in China—An Empirical Analysis. Healthcare 2021;10(1):77 View
  114. 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
  115. Jafarzadeh H, Pauleen D, Abedin E, Weerasinghe K, Taskin N, Coskun M, Mehmood R. Making sense of COVID-19 over time in New Zealand: Assessing the public conversation using Twitter. PLOS ONE 2021;16(12):e0259882 View
  116. Balli C, Guzel M, Bostanci E, Mishra A, Gong S. Sentimental Analysis of Twitter Users from Turkish Content with Natural Language Processing. Computational Intelligence and Neuroscience 2022;2022:1 View
  117. Yum S. The COVID-19 Response in North America. Disaster Medicine and Public Health Preparedness 2023;17 View
  118. Alhuzali H, Zhang T, Ananiadou S. Emotions and Topics Expressed on Twitter During the COVID-19 Pandemic in the United Kingdom: Comparative Geolocation and Text Mining Analysis. Journal of Medical Internet Research 2022;24(10):e40323 View
  119. Su Y, Li S, Huang F, Xue J, Zhu T. Exploring the Influencing Factors of COVID-19 Vaccination Willingness among Young Adults in China. International Journal of Environmental Research and Public Health 2023;20(5):3960 View
  120. Lloret-Pineda A, He Y, Haro J, Cristóbal-Narváez P. Types of Racism and Twitter Users’ Responses Amid the COVID-19 Outbreak: Content Analysis. JMIR Formative Research 2022;6(5):e29183 View
  121. Damiano A, Allen Catellier J. College students’ perceptions of COVID-19 conversations on social media. Journal of American College Health 2022:1 View
  122. Gour A, Aggarwal S, Kumar S. Lending ears to unheard voices: An empirical analysis of user‐generated content on social media. Production and Operations Management 2022;31(6):2457 View
  123. Ferawati K, Liew K, Aramaki E, Wakamiya S. Monitoring Mentions of COVID-19 Vaccine Side Effects on Japanese and Indonesian Twitter: Infodemiological Study. JMIR Infodemiology 2022;2(2):e39504 View
  124. Qi Y, Shabrina Z. Sentiment analysis using Twitter data: a comparative application of lexicon- and machine-learning-based approach. Social Network Analysis and Mining 2023;13(1) View
  125. Pettit R, Peng B, Yu P, Matos P, Greninger A, McCashin J, Amos C. Optimized workplace risk mitigation measures for SARS-CoV-2 in 2022. Scientific Reports 2023;13(1) View
  126. Mandl T, Jaki S, Mitera H, Schmidt F. Interdisciplinary Analysis of Science Communication on Social Media during the COVID-19 Crisis. Knowledge 2023;3(1):97 View
  127. Mir A, Rathinam S, Gul S. Public perception of COVID-19 vaccines from the digital footprints left on Twitter: analyzing positive, neutral and negative sentiments of Twitterati. Library Hi Tech 2022;40(2):340 View
  128. Cui J, Wang Z, Ho S, Cambria E. Survey on sentiment analysis: evolution of research methods and topics. Artificial Intelligence Review 2023 View
  129. Yan C, Law M, Nguyen S, Cheung J, Kong J. Comparing Public Sentiment Toward COVID-19 Vaccines Across Canadian Cities: Analysis of Comments on Reddit. Journal of Medical Internet Research 2021;23(9):e32685 View
  130. Chai Y, Palacios J, Wang J, Fan Y, Zheng S, Sasahara K. Measuring daily-life fear perception change: A computational study in the context of COVID-19. PLOS ONE 2022;17(12):e0278322 View
  131. Karabin M, Kyröläinen A, Kuperman V. Increase in Linguistic Complexity in Older Adults During COVID-19. Experimental Aging Research 2023:1 View
  132. Evans S, Jones R, Alkan E, Sichman J, Haque A, de Oliveira F, Mougouei D, Yan Z. The Emotional Impact of COVID-19 News Reporting: A Longitudinal Study Using Natural Language Processing. Human Behavior and Emerging Technologies 2023;2023:1 View
  133. Sharma B, Karunanayake I, Masood R, Ikram M. Don’t Be a Victim During a Pandemic! Analysing Security and Privacy Threats in Twitter During COVID-19. IEEE Access 2023;11:29769 View
  134. Biassoni F, Balzarotti S, Abati D, Salducco A, Gnerre M. Narratives on the present and the future in the time of COVID-19 pandemic: Uncertainty, subjective feeling and the role of positive anticipatory states. Frontiers in Communication 2023;8 View
  135. 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 View
  136. Xu H, Liu R, Luo Z, Xu M. COVID-19 Vaccine Sensing: Sentiment Analysis and Subject Distillation from Twitter Data. SSRN Electronic Journal 2022 View
  137. Lotto M, Hanjahanja-Phiri T, Padalko H, Oetomo A, Butt Z, Boger J, Millar J, Cruvinel T, Morita P. Ethical principles for infodemiology and infoveillance studies concerning infodemic management on social media. Frontiers in Public Health 2023;11 View
  138. Zakir Hussain I, Kaur J, Lotto M, Butt Z, Morita P. Tweeting for Health using Real-Time Mining and AI-Based Analytics: Design & Development of as Misinformation Data Ecosystem for Twitter (Preprint). Journal of Medical Internet Research 2022 View
  139. Davidson P, Muniandy T, Karmegam D. Perception of COVID-19 vaccination among Indian Twitter users: computational approach. Journal of Computational Social Science 2023 View
  140. Etienne D, Archambault P, Aziaka D, Chipenda-Dansokho S, Dubé E, Fallon C, Hakim H, Kindrachuk J, Krecoum D, MacDonald S, Ndjaboue R, Noubi M, Paquette J, Parent E, Witteman H. A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study. JMIR Formative Research 2023;7:e38430 View
  141. Stemmer M, Parmet Y, Ravid G. What are IBD Patients Talking About on Twitter? Using Natural Language Understanding to Investigate Patients’ Tweets. SN Computer Science 2023;4(4) View
  142. Rajkhowa P, Dsouza V, Kharel R, Cauvery K, Mallya B, Raksha D, Mrinalini V, Sharma P, Pattanshetty S, Narayanan P, Lahariya C, Brand H. Factors Influencing Monkeypox Vaccination: A Cue to Policy Implementation. Journal of Epidemiology and Global Health 2023 View
  143. Darad S, Krishnan S. Sentimental analysis of COVID-19 twitter data using deep learning and machine learning models. Ingenius 2023;(29):108 View
  144. Ujah O, Olaore P, Nnorom O, Ogbu C, Kirby R. Examining ethno-racial attitudes of the public in Twitter discourses related to the United States Supreme Court Dobbs vs. Jackson Women's Health Organization ruling: A machine learning approach. Frontiers in Global Women's Health 2023;4 View
  145. Rani S, Jain A. Optimizing healthcare system by amalgamation of text processing and deep learning: a systematic review. Multimedia Tools and Applications 2023 View
  146. Motwakel A, J. Alshahrani H, Q. A. Hassan A, Tarmissi K, S. Mehanna A, Yaseen I, Atta Abdelmageed A, Mahzari M. Sine Cosine Optimization with Deep Learning-Based Applied Linguistics for Sentiment Analysis on COVID-19 Tweets. Computers, Materials & Continua 2023;75(3):4767 View
  147. 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 View
  148. 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 View

Books/Policy Documents

  1. Chandran N, Anoop V. S. , Asharaf S. . Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media. View
  2. Karagkiozidou M, Koukaras P, Tjortjis C. Artificial Intelligence Applications and Innovations. View
  3. Küçük D, Arıcı N. Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media. View
  4. Shaikh S, Yayilgan S, Zoto E, Abomhara M. Intelligent Computing. View
  5. Gomez M, Ruipérez-Valiente J. Handbook of Research on Digital-Based Assessment and Innovative Practices in Education. View
  6. García-Contreras R, Muñoz-Chávez J, Valle-Cruz D, López-Chau A. Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media. View
  7. Chowdhury K, Sil A, Shukla S. Advances in Computing and Data Sciences. View
  8. Thakur O, Saritha S, Jain S. Machine Learning, Image Processing, Network Security and Data Sciences. View
  9. Ugwu C, Casarin S. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. View
  10. Ramzi N, Yusoff M, Noh N. Soft Computing in Data Science. View