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

Preprints (earlier versions) of this paper are available at, 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


  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 2023;38(11):2377 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 2023;43(6):1174 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 2023;19(3):317 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 2024;72(1):166 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;56(8):8469 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 2024;50(3):312 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;6(2):411 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. Morita P, Zakir Hussain I, Kaur J, Lotto M, Butt Z. Tweeting for Health Using Real-time Mining and Artificial Intelligence–Based Analytics: Design and Development of a Big Data Ecosystem for Detecting and Analyzing Misinformation on Twitter. Journal of Medical Internet Research 2023;25:e44356 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;6(2):541 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;13(2):226 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 2024;83(1):279 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;66(6):689 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;17(8) View
  149. Sitaula C, Shahi T. Multi-channel CNN to classify Nepali COVID-19 related tweets using hybrid features. Journal of Ambient Intelligence and Humanized Computing 2024;15(3):2047 View
  150. de Lima B, Baracho R, Mandl T, Porto P. Reactions to science communication: discovering social network topics using word embeddings and semantic knowledge. Social Network Analysis and Mining 2023;13(1) View
  151. Dong L, Liu Y. Frontiers of policy and governance research in a smart city and artificial intelligence: an advanced review based on natural language processing. Frontiers in Sustainable Cities 2023;5 View
  152. Li W, Haunert J, Knechtel J, Zhu J, Zhu Q, Dehbi Y. Social media insights on public perception and sentiment during and after disasters: The European floods in 2021 as a case study. Transactions in GIS 2023;27(6):1766 View
  153. Tian Y, Zhang W, Duan L, McDonald W, Osgood N. Comparison of pretrained transformer-based models for influenza and COVID-19 detection using social media text data in Saskatchewan, Canada. Frontiers in Digital Health 2023;5 View
  154. Owuor I, Hochmair H. Temporal Relationship between Daily Reports of COVID-19 Infections and Related GDELT and Tweet Mentions. Geographies 2023;3(3):584 View
  155. Kim H, Bae S, Park J. Research Trends on Cancer-Related Cognitive Impairment in Patients with Non-Central Nervous System Cancer: Text Network Analysis and Topic Modeling. Journal of Korean Academy of Fundamentals of Nursing 2023;30(3):313 View
  156. Jorge O, Remiro M, Lotto M, Zakir Hussain I, Moreira M, Morita P, Cruvinel T. Unveiling deception: Characterizing false amber necklace messages on Facebook. International Journal of Paediatric Dentistry 2024;34(3):302 View
  157. Luo H, Meng X, Zhao Y, Cai M. Rise of social bots: The impact of social bots on public opinion dynamics in public health emergencies from an information ecology perspective. Telematics and Informatics 2023;85:102051 View
  158. Gulzar R, Gul S, Verma M, Darzi M, Gulzar F, Shueb S. Analyzing the online public sentiments related to Russia-Ukraine war over Twitter. Global Knowledge, Memory and Communication 2023 View
  159. Korená K, Pártlová P. Social Media as a Tool of Building Reputation and Identity of National Parks. Communication Today 2023:116 View
  160. Thakur N, Cui S, Khanna K, Knieling V, Duggal Y, Shao M. Investigation of the Gender-Specific Discourse about Online Learning during COVID-19 on Twitter Using Sentiment Analysis, Subjectivity Analysis, and Toxicity Analysis. Computers 2023;12(11):221 View
  161. Meksawasdichai S, Lerksuthirat T, Ongphiphadhanakul B, Sriphrapradang C. Perspectives and Experiences of Patients With Thyroid Cancer at a Global Level: Retrospective Descriptive Study of Twitter Data. JMIR Cancer 2023;9:e48786 View
  162. Xia X, Zhang Y, Jiang W, Wu C. Staying Home, Tweeting Hope: Mixed Methods Study of Twitter Sentiment Geographical Index During US Stay-At-Home Orders. Journal of Medical Internet Research 2023;25:e45757 View
  163. Al-Qablan T, Mohd Noor M, Al-Betar M, Khader A. A survey on sentiment analysis and its applications. Neural Computing and Applications 2023;35(29):21567 View
  164. POYOI P, GASSIOT-MELIAN A, COROMINA L. Local food experiences before and after COVID-19: a sentiment analysis of EWOM. Tourism and hospitality management 2024;29(4):477 View
  165. Akande O, Lawrence M, Ogedebe P. Application of bidirectional LSTM deep learning technique for sentiment analysis of COVID-19 tweets: post-COVID vaccination era. Journal of Electrical Systems and Information Technology 2023;10(1) View
  166. Zhao Y, Zhang L, Zeng C, Lu W, Chen Y, Fan T. Construction of an aspect-level sentiment analysis model for online medical reviews. Information Processing & Management 2023;60(6):103513 View
  167. Chen J, Li P, Wang X, Yi K. Above management: Scale development and empirical testing for public opinion monitoring of marine pollution. Marine Pollution Bulletin 2023;192:114953 View
  168. Brandt M, Vallabha S, Turner-Zwinkels F. The Onset of the COVID-19 Pandemic Made People Feel Threatened, but Had a Limited Impact on Political Attitudes in the United States. Personality and Social Psychology Bulletin 2023 View
  169. Córdoba-Cabús A, García-Borrego M, Ceballos Y. Sentiment Analysis toward the COVID-19 Vaccine in the Main Latin American Media on Twitter: The Cases of Argentina, Chile, Colombia, Mexico, and Peru. Vaccines 2023;11(10):1592 View
  170. Christodoulakis N, Abdelkader W, Lokker C, Cotterchio M, Griffith L, Vanderloo L, Anderson L. Public Health Surveillance of Behavioral Cancer Risk Factors During the COVID-19 Pandemic: Sentiment and Emotion Analysis of Twitter Data. JMIR Formative Research 2023;7:e46874 View
  171. 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
  172. Zhang J, Pan Y, Lin H, Sun Z, Wu P, Tu J. Infodemic: Challenges and solutions in topic discovery and data process. Archives of Public Health 2023;81(1) View
  173. 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
  174. 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
  175. Lotto M, Zakir Hussain I, Kaur J, Butt Z, Cruvinel T, Morita P. Analysis of Fluoride-Free Content on Twitter: Topic Modeling Study. Journal of Medical Internet Research 2023;25:e44586 View
  176. Su M, Cheng D, Xu Y, Weng F. An improved BERT method for the evolution of network public opinion of major infectious diseases: Case Study of COVID-19. Expert Systems with Applications 2023;233:120938 View
  177. Miranda C, Sanchez-Torres G, Salcedo D. Exploring the Evolution of Sentiment in Spanish Pandemic Tweets: A Data Analysis Based on a Fine-Tuned BERT Architecture. Data 2023;8(6):96 View
  178. Jeong D, Hwang S, Kim J, Yu H, Park E. Public perspective on renewable and other energy resources: Evidence from social media big data and sentiment analysis. Energy Strategy Reviews 2023;50:101243 View
  179. 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 2023:1 View
  180. Gong W, Jiang L, Guo Q, Shen F. The role of family communication patterns in intergenerational COVID-19 discussions and preventive behaviors: a social cognitive approach. BMC Psychology 2023;11(1) View
  181. Fu J, Li C, Zhou C, Li W, Lai J, Deng S, Zhang Y, Guo Z, Wu Y. Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review. Journal of Medical Internet Research 2023;25:e43349 View
  182. Samaras L, García-Barriocanal E, Sicilia M. Sentiment analysis of COVID-19 cases in Greece using Twitter data. Expert Systems with Applications 2023;230:120577 View
  183. Zhang Q, Niu T, Yang J, Geng X, Lin Y. A study on the emotional and attitudinal behaviors of social media users under the sudden reopening policy of the Chinese government. Frontiers in Public Health 2023;11 View
  184. Sufi F, Alsulami M. Identifying drivers of COVID-19 vaccine sentiments for effective vaccination policy. Heliyon 2023;9(9):e19195 View
  185. Deng Z, Ma R, Wu M, Evans R. Netizens' concerns during COVID-19: a topic evolution analysis of Chinese social media platforms. Kybernetes 2023 View
  186. Zimba O, Gasparyan A. Designing, Conducting, and Reporting Survey Studies: A Primer for Researchers. Journal of Korean Medical Science 2023;38(48) View
  187. Galvez-Hernandez P, Gonzalez-Viana A, Gonzalez-de Paz L, Shankardass K, Muntaner C. Generating Contextual Variables From Web-Based Data for Health Research: Tutorial on Web Scraping, Text Mining, and Spatial Overlay Analysis. JMIR Public Health and Surveillance 2024;10:e50379 View
  188. Lopes A, Brotas A, Massarani L. A conversação pública acerca da vacina e da vacinação contra covid-19 no Twitter: um estudo infodemiológico. Intercom: Revista Brasileira de Ciências da Comunicação 2023;46 View
  189. Lopes A, Brotas A, Massarani L. The public conversation about vaccines and vaccination against covid-19 on Twitter: an infodemiological study. Intercom: Revista Brasileira de Ciências da Comunicação 2023;46 View
  190. Sandu A, Cotfas L, Delcea C, Crăciun L, Molănescu A. Sentiment Analysis in the Age of COVID-19: A Bibliometric Perspective. Information 2023;14(12):659 View
  191. 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
  192. Xin R, Lim Y. Bibliometric analysis of literature on social media trends during the COVID-19 pandemic. Online Information Review 2023 View
  193. Mukiri R, Burra V. A Novel Vision Transformer Model for Rumor Prediction in COVID-19 Data CT Images. Journal of Intelligent & Fuzzy Systems 2024;46(2):3635 View
  194. Borghouts J, Huang Y, Hopfer S, Li C, Mark G. Wording Matters: the Effect of Linguistic Characteristics and Political Ideology on Resharing of COVID-19 Vaccine Tweets. ACM Transactions on Computer-Human Interaction 2024 View
  195. Gyftopoulos S, Drosatos G, Fico G, Pecchia L, Kaldoudi E. Analysis of Pharmaceutical Companies’ Social Media Activity during the COVID-19 Pandemic and Its Impact on the Public. Behavioral Sciences 2024;14(2):128 View
  196. Chandrasekaran R, Konaraddi K, Sharma S, Moustakas E. Text-Mining and Video Analytics of COVID-19 Narratives Shared by Patients on YouTube. Journal of Medical Systems 2024;48(1) View
  197. 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
  198. Schenkel M. Health emergencies, science contrarianism and populism: A scoping review. Social Science & Medicine 2024;346:116691 View
  199. Wang H, Li Y, Ning X. News Coverage of COVID-19 on Social Media and Public’s Negative Emotions: A Computational Study (Preprint). Journal of Medical Internet Research 2023 View
  200. Zhang A, Ong C. “We Are Bulletproof”: The Transcultural Power of Fandom in #StopAsianHate. Sociological Inquiry 2024;94(2):391 View
  201. Kusumaningrum R, Khoerunnisa S, Khadijah K, Syafrudin M. Exploring Community Awareness of Mangrove Ecosystem Preservation through Sentence-BERT and K-Means Clustering. Information 2024;15(3):165 View
  202. Lin B, Zou L, Zhao B, Huang X, Cai H, Yang M, Zhou B. Sensing the pulse of the pandemic: unveiling the geographical and demographic disparities of public sentiment toward COVID-19 through social media. Cartography and Geographic Information Science 2024:1 View
  203. Shahbazi M, Bunker D. Social media trust: Fighting misinformation in the time of crisis. International Journal of Information Management 2024;77:102780 View
  204. Molenaar A, Lukose D, Brennan L, Jenkins E, McCaffrey T. Using Natural Language Processing to Explore Social Media Opinions on Food Security: Sentiment Analysis and Topic Modeling Study. Journal of Medical Internet Research 2024;26:e47826 View
  205. Jacob N, Viswanatham V. Sentiment Analysis Using Improved Atom Search Optimizer With a Simulated Annealing and ReLU Based Gated Recurrent Unit. IEEE Access 2024;12:38944 View
  206. Esquirol B, Prignano L, Díaz-Guilera A, Cozzo E. Analyzing user activity on Twitter during long-lasting crisis events: a case study of the Covid-19 crisis in Spain. Social Network Analysis and Mining 2024;14(1) View
  207. Sandu A, Cotfas L, Stănescu A, Delcea C. A Bibliometric Analysis of Text Mining: Exploring the Use of Natural Language Processing in Social Media Research. Applied Sciences 2024;14(8):3144 View
  208. Whitfield C, Liu Y, Anwar M. Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by Natural Language Processing. Journal of Racial and Ethnic Health Disparities 2024 View
  209. Chepo M, Martin S, Déom N, Khalid A, Vindrola-Padros C. Twitter Analysis of Health Care Workers’ Sentiment and Discourse Regarding Post–COVID-19 Condition in Children and Young People: Mixed Methods Study. Journal of Medical Internet Research 2024;26:e50139 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
  11. Martinis M, Scarpino I, Zucco C, Cannataro M. Computational Science – ICCS 2023. View
  12. Gupta A, Tadanki N, Berry N, Bardae R, Harikrishnan R, Wagle S. Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security. View
  13. Sakiyama K, de Souza Rodrigues L, Nogueira B, Matsubara E, Romero R. Intelligent Systems. View
  14. Denecke K. Sentiment Analysis in the Medical Domain. View
  15. Vasudev R, Dahikar P, Jain A, Patil N. Big Data, Machine Learning, and Applications. View
  16. Osop H, Wong J, Lwin S, Lee C. Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration. View
  17. de Lima B, Baracho R, Mandl T. Information Systems and Technologies. View