Published on in Vol 3, No 2 (2017): Apr-Jun

What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, and Prevention

What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, and Prevention

What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, and Prevention

Journals

  1. Jia S. Leisure Motivation and Satisfaction: A Text Mining of Yoga Centres, Yoga Consumers, and Their Interactions. Sustainability 2018;10(12):4458 View
  2. Khatua A, Khatua A, Cambria E. A tale of two epidemics: Contextual Word2Vec for classifying twitter streams during outbreaks. Information Processing & Management 2019;56(1):247 View
  3. Jia S. Motivation and satisfaction of Chinese and U.S. tourists in restaurants: A cross-cultural text mining of online reviews. Tourism Management 2020;78:104071 View
  4. López-Goñi I, Sánchez-Angulo M. Social networks as a tool for science communication and public engagement: focus on Twitter. FEMS Microbiology Letters 2018;365(2) View
  5. Gianfredi V, Bragazzi N, Nucci D, Martini M, Rosselli R, Minelli L, Moretti M. Harnessing Big Data for Communicable Tropical and Sub-Tropical Disorders: Implications From a Systematic Review of the Literature. Frontiers in Public Health 2018;6 View
  6. Chang Y, Chiang W, Wang W, Lin C, Hung L, Tsai Y, Chen Y. Assessing Epidemic Diseases and Public Opinion through Popular Search Behavior Using Non-English Language Google Trends (Preprint). JMIR Public Health and Surveillance 2018 View
  7. Saura J, Reyes-Menendez A, Thomas S. Gaining a deeper understanding of nutrition using social networks and user-generated content. Internet Interventions 2020;20:100312 View
  8. Mamidi R, Miller M, Banerjee T, Romine W, Sheth A. Identifying Key Topics Bearing Negative Sentiment on Twitter: Insights Concerning the 2015-2016 Zika Epidemic. JMIR Public Health and Surveillance 2019;5(2):e11036 View
  9. Cook N, Mullins A, Gautam R, Medi S, Prince C, Tyagi N, Kommineni J. Evaluating Patient Experiences in Dry Eye Disease Through Social Media Listening Research. Ophthalmology and Therapy 2019;8(3):407 View
  10. Wang S, Patterson O, Gagne J, Brown J, Ball R, Jonsson P, Wright A, Zhou L, Goettsch W, Bate A. Transparent Reporting on Research Using Unstructured Electronic Health Record Data to Generate ‘Real World’ Evidence of Comparative Effectiveness and Safety. Drug Safety 2019;42(11):1297 View
  11. Valente P, Morin C, Roy M, Mercier A, Atlani-Duault L. Sexual transmission of Zika virus on Twitter: A depoliticised epidemic. Global Public Health 2020;15(11):1689 View
  12. Albalawi Y, Nikolov N, Buckley J. Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis. Journal of Medical Internet Research 2019;21(10):e14731 View
  13. Deiner M, Fathy C, Kim J, Niemeyer K, Ramirez D, Ackley S, Liu F, Lietman T, Porco T. Facebook and Twitter vaccine sentiment in response to measles outbreaks. Health Informatics Journal 2019;25(3):1116 View
  14. Blbas H, Aziz K, Nejad S, Barzinjy A. Phenomenon of depression and anxiety related to precautions for prevention among population during the outbreak of COVID-19 in Kurdistan Region of Iraq: based on questionnaire survey. Journal of Public Health 2022;30(3):567 View
  15. Jia S. Toward a better fitness club: Evidence from exerciser online rating and review using latent Dirichlet allocation and support vector machine. International Journal of Market Research 2019;61(1):64 View
  16. Herrera-Peco I, de la Torre-Montero J. Preface of Special Issue “Cares in the Age of Communication: Health Education and Healthy Lifestyles”: Social Media and Health Communication in a Pandemic?. European Journal of Investigation in Health, Psychology and Education 2020;10(2):575 View
  17. Krittanawong C, Narasimhan B, Virk H, Narasimhan H, Hahn J, Wang Z, Tang W. Misinformation Dissemination in Twitter in the COVID-19 Era. The American Journal of Medicine 2020;133(12):1367 View
  18. Chen T, Dredze M. Vaccine Images on Twitter: Analysis of What Images are Shared. Journal of Medical Internet Research 2018;20(4):e130 View
  19. Barata G, Shores K, Alperin J, Emmert-Streib F. Local chatter or international buzz? Language differences on posts about Zika research on Twitter and Facebook. PLOS ONE 2018;13(1):e0190482 View
  20. Pruss D, Fujinuma Y, Daughton A, Paul M, Arnot B, Albers Szafir D, Boyd-Graber J, Xia F. Zika discourse in the Americas: A multilingual topic analysis of Twitter. PLOS ONE 2019;14(5):e0216922 View
  21. Safarnejad L, Xu Q, Ge Y, Bagavathi A, Krishnan S, Chen S. Identifying Influential Factors in the Discussion Dynamics of Emerging Health Issues on Social Media: Computational Study. JMIR Public Health and Surveillance 2020;6(3):e17175 View
  22. Chen S, Xu Q, Buchenberger J, Bagavathi A, Fair G, Shaikh S, Krishnan S. Dynamics of Health Agency Response and Public Engagement in Public Health Emergency: A Case Study of CDC Tweeting Patterns During the 2016 Zika Epidemic. JMIR Public Health and Surveillance 2018;4(4):e10827 View
  23. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  24. Chang Y, Chiang W, Wang W, Lin C, Hung L, Tsai Y, Suen J, Chen Y. Google Trends-based non-English language query data and epidemic diseases: a cross-sectional study of the popular search behaviour in Taiwan. BMJ Open 2020;10(7):e034156 View
  25. Barata G, Shores K, Alperin J. Local Chatter or International Buzz? Language Differences on Posts About Zika Research on Twitter and Facebook. SSRN Electronic Journal 2017 View
  26. Daughton A, Paul M. Identifying Protective Health Behaviors on Twitter: Observational Study of Travel Advisories and Zika Virus. Journal of Medical Internet Research 2019;21(5):e13090 View
  27. Zhang J, Chen Y, Zhao Y, Wolfram D, Ma F. Public health and social media: A study of Zika virus‐related posts on Yahoo! Answers. Journal of the Association for Information Science and Technology 2020;71(3):282 View
  28. Roy M, Moreau N, Rousseau C, Mercier A, Wilson A, Atlani-Duault L. Ebola and Localized Blame on Social Media: Analysis of Twitter and Facebook Conversations During the 2014–2015 Ebola Epidemic. Culture, Medicine, and Psychiatry 2020;44(1):56 View
  29. Park H, Jung H, On J, Park S, Kang H. Digital Epidemiology: Use of Digital Data Collected for Non-epidemiological Purposes in Epidemiological Studies. Healthcare Informatics Research 2018;24(4):253 View
  30. Masri S, Jia J, Li C, Zhou G, Lee M, Yan G, Wu J. Use of Twitter data to improve Zika virus surveillance in the United States during the 2016 epidemic. BMC Public Health 2019;19(1) View
  31. Saura J, Palos-Sanchez P, Grilo A. Detecting Indicators for Startup Business Success: Sentiment Analysis Using Text Data Mining. Sustainability 2019;11(3):917 View
  32. Paul M, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1 View
  33. Wicke P, Bolognesi M, Athanasopoulos P. Framing COVID-19: How we conceptualize and discuss the pandemic on Twitter. PLOS ONE 2020;15(9):e0240010 View
  34. Wicke P, Bolognesi M. Covid-19 Discourse on Twitter: How the Topics, Sentiments, Subjectivity, and Figurative Frames Changed Over Time. Frontiers in Communication 2021;6 View
  35. Heyerdahl L, Vray M, Leger V, Le Fouler L, Antouly J, Troit V, Giles-Vernick T. Evaluating the motivation of Red Cross Health volunteers in the COVID-19 pandemic: a mixed-methods study protocol. BMJ Open 2021;11(1):e042579 View
  36. 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
  37. Lyu J, Luli G. Understanding the Public Discussion About the Centers for Disease Control and Prevention During the COVID-19 Pandemic Using Twitter Data: Text Mining Analysis Study. Journal of Medical Internet Research 2021;23(2):e25108 View
  38. Amara A, Hadj Taieb M, Ben Aouicha M. Multilingual topic modeling for tracking COVID-19 trends based on Facebook data analysis. Applied Intelligence 2021;51(5):3052 View
  39. 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
  40. Jia S, Wu B, Zhou S. Topic modelling and opinion mining of user generated content on the internet using machine learning: An analysis of postpartum care centres in Shanghai. Journal of Intelligent & Fuzzy Systems 2021;41(3):4661 View
  41. Alvarez-Galvez J, Suarez-Lledo V, Rojas-Garcia A. Determinants of Infodemics During Disease Outbreaks: A Systematic Review. Frontiers in Public Health 2021;9 View
  42. AGRAWAL A, GUPTA A. The Utility of Social Media during an Emerging Infectious Diseases Crisis: A Systematic Review of Literature. Journal of Microbiology and Infectious Diseases 2020:188 View
  43. Ke Q, Du J, Ji L. Toward a conceptual framework of health crisis information needs: an analysis of COVID-19 questions in a Chinese social Q&A website. Journal of Documentation 2021;77(4):851 View
  44. Shahi G, Dirkson A, Majchrzak T. An exploratory study of COVID-19 misinformation on Twitter. Online Social Networks and Media 2021;22:100104 View
  45. 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
  46. Chowdhury N, Khalid A, Turin T. Understanding misinformation infodemic during public health emergencies due to large-scale disease outbreaks: a rapid review. Journal of Public Health 2023;31(4):553 View
  47. Jia S. Analyzing Restaurant Customers’ Evolution of Dining Patterns and Satisfaction during COVID-19 for Sustainable Business Insights. Sustainability 2021;13(9):4981 View
  48. Shah A, Naqvi R, Jeong O. Detecting Topic and Sentiment Trends in Physician Rating Websites: Analysis of Online Reviews Using 3-Wave Datasets. International Journal of Environmental Research and Public Health 2021;18(9):4743 View
  49. Miller M, Romine W, Oroszi T. Public Discussion of Anthrax on Twitter: Using Machine Learning to Identify Relevant Topics and Events. JMIR Public Health and Surveillance 2021;7(6):e27976 View
  50. Fairie P, Zhang Z, D'Souza A, Walsh T, Quan H, Santana M. Categorising patient concerns using natural language processing techniques. BMJ Health & Care Informatics 2021;28(1):e100274 View
  51. Zahid S, Shams Malick R, Sagri M. Network Dynamics of COVID-19 Fake and True News Diffusion Networks. Journal of Information & Knowledge Management 2022;21(Supp01) View
  52. Bonifazi G, Corradini E, Ursino D, Virgili L. New Approaches to Extract Information From Posts on COVID-19 Published on Reddit. International Journal of Information Technology & Decision Making 2022;21(05):1385 View
  53. Kandasamy G, Almaghaslah D, Almanasef M, Vasudevan R, Easwaran V. An evaluation of the psychological impact of COVID‐19 and the precautionary measure of social isolation on adults in the Asir region, Saudi Arabia. International Journal of Clinical Practice 2021;75(11) View
  54. Zuo C, Banerjee R, Chaleshtori F, Shirazi H, Ray I. Seeing Should Probably Not Be Believing: The Role of Deceptive Support in COVID-19 Misinformation on Twitter. Journal of Data and Information Quality 2023;15(1):1 View
  55. 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
  56. Zhang G, Giachanou A, Rosso P. SceneFND: Multimodal fake news detection by modelling scene context information. Journal of Information Science 2024;50(2):355 View
  57. Bravo C, Castells V, Zietek-Gutsch S, Bodin P, Molony C, Frühwein M. Using social media listening and data mining to understand travellers’ perspectives on travel disease risks and vaccine-related attitudes and behaviours. Journal of Travel Medicine 2022;29(2) View
  58. Alshare K, Moqbel M, Merhi M. The double-edged sword of social media usage during the COVID-19 pandemic: demographical and cultural analyses. Journal of Enterprise Information Management 2023;36(1):197 View
  59. Recuero-Virto N, Valilla-Arróspide C. Forecasting the next revolution: food technology’s impact on consumers' acceptance and satisfaction. British Food Journal 2022;124(12):4339 View
  60. Nikookar S, Maleki A, Fazeli-Dinan M, Shabani Kordshouli R, Enayati A. Entomological Surveillance of the Invasive Aedes Species at Higher-Priority Entry Points in Northern Iran: Exploratory Report on a Field Study. JMIR Public Health and Surveillance 2022;8(10):e38647 View
  61. Chen S, Yin S, Guo Y, Ge Y, Janies D, Dulin M, Brown C, Robinson P, Zhang D. Content and sentiment surveillance (CSI): A critical component for modeling modern epidemics. Frontiers in Public Health 2023;11 View
  62. Burwell E, Agarwal A, Romine W. Understanding communication about the COVID-19 vaccines: analysis of emergent sentiments and topics of discussion on Twitter during the initial phase of the vaccine rollout. International Journal of Science Education, Part B 2024;14(1):18 View
  63. 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
  64. Alnashwan R, O’Riordan A, Sorensen H. Multiple-Perspective Data-Driven Analysis of Online Health Communities. Healthcare 2023;11(20):2723 View
  65. Sloesen B, O'Brien P, Verma H, Asaithambi S, Parashar N, Mothe R, Shaikh J, Syntosi A. Patient Experiences and Insights on Chronic Ocular Pain: Social Media Listening Study. JMIR Formative Research 2024;8:e47245 View
  66. Gómez Punzón J, Recuero-Virto N. The Influence of Museum User Generated Content to Improve the Experience Design. SSRN Electronic Journal 2024 View
  67. Recuero-Virto N, Valilla C. Forecasting the Next Revolution: Food Technology’s Impact on Consumers' Acceptance and Satisfaction. SSRN Electronic Journal 2024 View
  68. Melo C, Mageste L, Guaraldo L, Paula D, Wakimoto M. Use of Digital Tools in Arbovirus Surveillance: Scoping Review. Journal of Medical Internet Research 2024;26:e57476 View
  69. Kumble S, Diddi P, Bien-Aimé S. Understanding content dissemination on sensemaking: WHO’s social listening strategy on X during the initial phase of COVID-19. Online Media and Global Communication 2024 View
  70. Hoffstädt H, Verhoef M, Akkermans A, van der Steen J, Stoppelenburg A, de Vries S, de Graaf E, Teunissen S, Hartog I, van der Linden Y, Frey R. “Are you listening?”: Experiences shared online by family caregivers of patients in the palliative phase during the Covid-19-pandemic. PLOS ONE 2024;19(11):e0310624 View

Books/Policy Documents

  1. Kho S, Padhee S, Bajaj G, Thirunarayan K, Sheth A. Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining. View
  2. da Silva D, Goncalves G, dos Santos S, Pugliese V, Navas J, de Barros Santana R, Queiroz F, Dias L, da Cunha A, Tasinaffo P. Information Technology – New Generations. View
  3. Sheth A, Purohit H, Smith G, Brunn J, Jadhav A, Kapanipathi P, Lu C, Wang W. Encyclopedia of Social Network Analysis and Mining. View
  4. Sheth A, Purohit H, Smith G, Brunn J, Jadhav A, Kapanipathi P, Lu C, Wang W. Encyclopedia of Social Network Analysis and Mining. View
  5. Gilbert J, Niu J, de Montigny S, Ng V, Rees E. AI for Disease Surveillance and Pandemic Intelligence. View
  6. Recuero-Virto N. COVID-19 and a World of Ad Hoc Geographies. View
  7. Jabeen F, Khan F, Shah S, Ahmad B, Jabeen S. Advances in Cybersecurity, Cybercrimes, and Smart Emerging Technologies. View
  8. Zuo C, Wang C, Banerjee R. Advanced Data Mining and Applications. View