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

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

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

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

Journals

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  131. Ghanem A, Asaad C, Hafidi H, Moukafih Y, Guermah B, Sbihi N, Zakroum M, Ghogho M, Dairi M, Cherqaoui M, Baina K. Real-Time Infoveillance of Moroccan Social Media Users’ Sentiments towards the COVID-19 Pandemic and Its Management. International Journal of Environmental Research and Public Health 2021;18(22):12172 View
  132. Mwangale Kiptinness E, Okoye J, Shiri R. Media coverage of the novel Coronavirus (Covid-19) in Kenya and Tanzania: Content analysis of newspaper articles in East Africa. Cogent Medicine 2021;8(1) View
  133. Yuan L, Wang M, Umakanthan S. The emotion bias of health product consumers in the context of COVID-19. PLOS ONE 2022;17(11):e0278219 View
  134. Obreja D. Narrative communication regarding the Covid-19 vaccine: a thematic analysis of comments on Romanian official Facebook page “RO Vaccinare”. SN Social Sciences 2022;2(8) View
  135. Fernandez G, Maione C, Zaballa K, Bonnici N, Spitzberg B, Carter J, Yang H, McKew J, Bonora F, Ghodke S, Jin C, De Ocampo R, Kepner W, Tsou M. The Geography of Covid-19 Spread in Italy Using Social Media and Geospatial Data Analytics. The International Journal of Intelligence, Security, and Public Affairs 2021;23(3):228 View
  136. Vyas P, Reisslein M, Rimal B, Vyas G, Basyal G, Muzumdar P. Automated Classification of Societal Sentiments on Twitter With Machine Learning. IEEE Transactions on Technology and Society 2022;3(2):100 View
  137. Ng Q, Yau C, Lim Y, Wong L, Liew T. Public sentiment on the global outbreak of monkeypox: an unsupervised machine learning analysis of 352,182 twitter posts. Public Health 2022;213:1 View
  138. Singhal A, Baxi M, Mago V. Synergy Between Public and Private Health Care Organizations During COVID-19 on Twitter: Sentiment and Engagement Analysis Using Forecasting Models. JMIR Medical Informatics 2022;10(8):e37829 View
  139. Kubacka M, Luczys P, Modrzyk A, Stamm A. Pandemic rage: Everyday frustrations in times of the COVID-19 crisis. Current Sociology 2021:001139212110501 View
  140. Choi D. The multifaceted impact of social media on risk, behavior, and negative emotions during the COVID-19 outbreak in South Korea. Asian Journal of Communication 2021;31(5):337 View
  141. Wolaver A, Doces J. The impact of COVID‐19 and political identification on framing bias in an infectious disease experiment: The frame reigns supreme. Social Science Quarterly 2021;102(6):2459 View
  142. León-Sandoval E, Zareei M, Barbosa-Santillán L, Falcón Morales L, Pareja Lora A, Ochoa Ruiz G, Hošovský A. Monitoring the Emotional Response to the COVID-19 Pandemic Using Sentiment Analysis: A Case Study in Mexico. Computational Intelligence and Neuroscience 2022;2022:1 View
  143. Fattoh I, Kamal Alsheref F, Ead W, Youssef A, Alonso-Betanzos A. Semantic Sentiment Classification for COVID-19 Tweets Using Universal Sentence Encoder. Computational Intelligence and Neuroscience 2022;2022:1 View
  144. Wang R, Zhang H. Who spread COVID-19 (mis)information online? Differential informedness, psychological mechanisms, and intervention strategies. Computers in Human Behavior 2023;138:107486 View
  145. Zahry N, McCluskey M, Ling J. Risk governance during the COVID‐19 pandemic: A quantitative content analysis of governors' narratives on twitter. Journal of Contingencies and Crisis Management 2023;31(1):77 View
  146. ‘Ali N, Rosenberg D. Understanding the consideration of strategies for coping with locality violence in Arab society in Israel. Security Journal 2023 View
  147. Kyröläinen A, Luke J, Libben G, Kuperman V. Valence norms for 3,600 English words collected during the COVID-19 pandemic: Effects of age and the pandemic. Behavior Research Methods 2021;54(5):2445 View
  148. Khraisat B, Toubasi A, AlZoubi L, Al-Sayegh T, Mansour A. Meta-analysis of prevalence: the psychological sequelae among COVID-19 survivors. International Journal of Psychiatry in Clinical Practice 2022;26(3):234 View
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  150. Zhang Q, Yi G, Chen L, He W, Kaddoura S. Sentiment analysis and causal learning of COVID-19 tweets prior to the rollout of vaccines. PLOS ONE 2023;18(2):e0277878 View
  151. Huang C, Bandyopadhyay A, Fan W, Miller A, Gilbertson-White S, Chen Z. Mental toll on working women during the COVID-19 pandemic: An exploratory study using Reddit data. PLOS ONE 2023;18(1):e0280049 View
  152. Beliga S, Martinčić-Ipšić S, Matešić M, Petrijevčanin Vuksanović I, Meštrović A. Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing. JMIR Public Health and Surveillance 2021;7(12):e31540 View
  153. Stevens H, Rasul M, Oh Y. Emotions and Incivility in Vaccine Mandate Discourse: Natural Language Processing Insights. JMIR Infodemiology 2022;2(2):e37635 View
  154. Parthasarathi , Kumari G. Religious Tweets During COVID-19: Qualitative Analysis of Articulation of Ideas of Netizens. Media Watch 2022;13(1):104 View
  155. Lee E, Zheng H, Goh D, Lee C, Theng Y. Examining COVID-19 Tweet Diffusion Using an Integrated Social Amplification of Risk and Issue-Attention Cycle Framework. Health Communication 2023:1 View
  156. Lorenzoni V, Andreozzi G, Bazzani A, Casigliani V, Pirri S, Tavoschi L, Turchetti G. How Italy Tweeted about COVID-19: Detecting Reactions to the Pandemic from Social Media. International Journal of Environmental Research and Public Health 2022;19(13):7785 View
  157. Jabeen A, Afzal S, Maqsood M, Mehmood I, Yasmin S, Tabish Niaz M, Nam Y. An LSTM Based Forecasting for Major Stock Sectors Using COVID Sentiment. Computers, Materials & Continua 2021;67(1):1191 View
  158. Pourkarim M, Nayebzadeh S, Alavian S, Hataminasab S. Digital Marketing: A Unique Multidisciplinary Approach towards the Elimination of Viral Hepatitis. Pathogens 2022;11(6):626 View
  159. Zhang W, Li L, Mou J, Zhang M, Cheng X, Xia H. Mediating Effects of Attitudes, Risk Perceptions, and Negative Emotions on Coping Behaviors. Journal of Organizational and End User Computing 2022;34(6):1 View
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  161. Mazzuca C, Falcinelli I, Michalland A, Tummolini L, Borghi A. Differences and similarities in the conceptualization of COVID-19 and other diseases in the first Italian lockdown. Scientific Reports 2021;11(1) View
  162. Hopkins S, Stark A, Zinoviev D, Tousignant O, Fireman G. College student expression on Twitter during the COVID-19 pandemic. Journal of American College Health 2022:1 View
  163. Choi R, Nagappan A, Kopyto D, Wexler A. Pregnant at the start of the pandemic: a content analysis of COVID-19-related posts on online pregnancy discussion boards. BMC Pregnancy and Childbirth 2022;22(1) View
  164. Houlden S, Hodson J, Veletsianos G, Thompson C, Reid D. Inoculating an Infodemic: An Ecological Approach to Understanding Engagement With COVID-19 Online Information. American Behavioral Scientist 2021;65(14):1990 View
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  166. Altan H, Coşgun A. Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study. BMC Oral Health 2021;21(1) View
  167. Xu H, Liu R, Luo Z, Xu M. COVID-19 vaccine sensing: Sentiment analysis and subject distillation from twitter data. Telematics and Informatics Reports 2022;8:100016 View
  168. Houlden S, Veletsianos G, Hodson J, Reid D, Thompson C. COVID-19 health misinformation: using design-based research to develop a theoretical framework for intervention. Health Education 2022;122(5):506 View
  169. F. Ibrahim A, Hassaballah M, A. Ali A, Nam Y, A. Ibrahim I. COVID19 Outbreak: A Hierarchical Framework for User Sentiment Analysis. Computers, Materials & Continua 2022;70(2):2507 View
  170. Kada A, Chouikh A, Mellouli S, Prashad A, Straus S, Fahim C, Gaito S. An exploration of Canadian government officials’ COVID-19 messages and the public’s reaction using social media data. PLOS ONE 2022;17(9):e0273153 View
  171. Fernandez G, Maione C, Yang H, Zaballa K, Bonnici N, Carter J, Spitzberg B, Jin C, Tsou M. Social Network Analysis of COVID-19 Sentiments: 10 Metropolitan Cities in Italy. International Journal of Environmental Research and Public Health 2022;19(13):7720 View
  172. Drescher L, Roosen J, Aue K, Dressel K, Schär W, Götz A. The Spread of COVID-19 Crisis Communication by German Public Authorities and Experts on Twitter: Quantitative Content Analysis. JMIR Public Health and Surveillance 2021;7(12):e31834 View
  173. Jain V, Kashyap K. Multilayer hybrid ensemble machine learning model for analysis of Covid-19 vaccine sentiments. Journal of Intelligent & Fuzzy Systems 2022;43(5):6307 View
  174. Waggoner P, Shapiro R, Frederick S, Gong M. Uncovering the Online Social Structure Surrounding COVID-19. Journal of Social Computing 2021;2(2):157 View
  175. Karabin M, Kyröläinen A, Kuperman V. Increase in Linguistic Complexity in Older Adults During COVID-19. Experimental Aging Research 2023:1 View
  176. Rosato C, Moore R, Carter M, Heap J, Harris J, Storopoli J, Maskell S. Extracting Self-Reported COVID-19 Symptom Tweets and Twitter Movement Mobility Origin/Destination Matrices to Inform Disease Models. Information 2023;14(3):170 View
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  179. Handayani P, Zagatti G, Kefi H, Bressan S. Impact of Social Media Usage on Users’ COVID-19 Protective Behavior: Survey Study in Indonesia. JMIR Formative Research 2023;7:e46661 View
  180. Amores J, Blanco-Herrero D, Arcila-Calderón C. The Conversation around COVID-19 on Twitter—Sentiment Analysis and Topic Modelling to Analyse Tweets Published in English during the First Wave of the Pandemic. Journalism and Media 2023;4(2):467 View
  181. Muitana G, Amato C. Topics, concerns, and feelings commented on Facebook after the first death by COVID-19 in Mozambique. Revista de Investigación e Innovación en Ciencias de la Salud 2023;5(1):press View
  182. Sukhavasi N, Misra J, Kaulgud V, Podder S. Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19. Journal of Computational Social Science 2023 View
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  185. Das D, Pal S, Jena L. Emotional Labour During the COVID-19 Pandemic—Current Inquiry and Suggested Future Research Directions. Management and Labour Studies 2023:0258042X2311679 View
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Books/Policy Documents

  1. Koinig I. Risk Management. View
  2. Wright K. Communicating Science in Times of Crisis. View
  3. Alsoubai A, Song J, Razi A, Dacre P, Wisniewski P. Social Computing and Social Media: Applications in Marketing, Learning, and Health. View
  4. Yan Y, Chin W, Leong C, Wang Y, Feng C. Mapping COVID-19 in Space and Time. View
  5. Babić K, Petrović M, Beliga S, Martinčić-Ipšić S, Jarynowski A, Meštrović A. Proceedings of Sixth International Congress on Information and Communication Technology. View
  6. Fernandez G, Maione C, Zaballa K, Bonnici N, Spitzberg B, Carter J, Yang H, McKew J, Bonora F, Ghodke S, Jin C, De Ocampo R, Kepner W, Tsou M. Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics. View
  7. Miliou I, Pavlopoulos J, Papapetrou P. Discovery Science. View
  8. Bogović P, Meštrović A, Martinčić-Ipšić S. Information and Software Technologies. View
  9. Rushee K, Rahim M, Levula A, Mahdavi M. Advanced Information Networking and Applications. View
  10. Zhao Q, Nie L, Xu X. Comparative Studies on Pandemic Control Policies and the Resilience of Society. View
  11. Koinig I. Advances in Advertising Research (Vol. XII). View