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Citing this Article

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Published on 20.04.17 in Vol 3, No 2 (2017): Apr-Jun

This paper is in the following e-collection/theme issue:

Works citing "Zika in Twitter: Temporal Variations of Locations, Actors, and Concepts"

Anthony Stefanidis, Emily Vraga, Georgios Lamprianidis, Jacek Radzikowski, Paul L Delamater, Kathryn H Jacobsen, Dieter Pfoser, Arie Croitoru, Andrew Crooks

JMIR Public Health Surveill 2017 (Apr 20); 3(2):e22 

According to Crossref, the following articles are citing this article (DOI 10.2196/publichealth.6925):

(note that this is only a small subset of citations)

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  5. Aschwanden A, Demir C, Hinselmann R, Kasser S, Rohrer A. Zika and travel: Public health implications and communications for blood donors, sperm donors and pregnant women. Travel Medicine and Infectious Disease 2018;21:77
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  6. 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
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  9. Xu X, Litchman ML, Gee PM, Whatcott W, Chacon L, Holmes J, Srinivasan SS. Predicting Prediabetes Through Facebook Postings: Protocol for a Mixed-Methods Study. JMIR Research Protocols 2018;7(12):e10720
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  10. Paul MJ, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1
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  12. Owuor I, Hochmair H. An Overview of Social Media Apps and their Potential Role in Geospatial Research. ISPRS International Journal of Geo-Information 2020;9(9):526
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  13. 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
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  14. Eke R, Li T, Bond K, Ho A, Graves L. Viewing Trends and Users’ Perceptions of the Effect of Sleep-Aiding Music on YouTube: Quantification and Thematic Content Analysis. Journal of Medical Internet Research 2020;22(8):e15697
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  17. . Geo‐text data and data‐driven geospatial semantics. Geography Compass 2018;12(11)
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  19. Burger , Oz , Kennedy , Crooks . Computational Social Science of Disasters: Opportunities and Challenges. Future Internet 2019;11(5):103
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  21. Barata G, Shores K, Alperin JP. Local Chatter or International Buzz? Language Differences on Posts About Zika Research on Twitter and Facebook. SSRN Electronic Journal 2017;
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  22. Vraga EK, Jacobsen KH. Strategies for Effective Health Communication during the Coronavirus Pandemic and Future Emerging Infectious Disease Events. World Medical & Health Policy 2020;12(3):233
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  23. Anderson EJ, Ernst KC, Martins FF, Martins CDS, Koss MP. Women’s Health Perceptions and Beliefs Related to Zika Virus Exposure during the 2016 Outbreak in Northern Brazil. The American Journal of Tropical Medicine and Hygiene 2020;102(3):629
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  24. Barata G, Shores K, Alperin JP, 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
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  27. . Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
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  28. Litchman ML, Wawrzynski SE, Woodruff WS, Arrington JB, Nguyen QC, Gee PM. Continuous Glucose Monitoring in the Real World Using Photosurveillance of #Dexcom on Instagram: Exploratory Mixed Methods Study. JMIR Public Health and Surveillance 2019;5(2):e11024
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  29. 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
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  32. Essam BA, Abdo MS. How Do Arab Tweeters Perceive the COVID-19 Pandemic?. Journal of Psycholinguistic Research 2021;50(3):507
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  33. Lopez BE, Magliocca NR, Crooks AT. Challenges and Opportunities of Social Media Data for Socio-Environmental Systems Research. Land 2019;8(7):107
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  34. Plaster AN, Painter JE, Tjersland DH, Jacobsen KH. University Students’ Knowledge, Attitudes, and Sources of Information About Zika Virus. Journal of Community Health 2018;43(4):647
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  35. 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)
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  36. Pruss D, Fujinuma Y, Daughton AR, Paul MJ, 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
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  37. Daughton AR, Paul MJ. Identifying Protective Health Behaviors on Twitter: Observational Study of Travel Advisories and Zika Virus. Journal of Medical Internet Research 2019;21(5):e13090
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  38. Fung IC, Jackson AM, Mullican LA, Blankenship EB, Goff ME, Guinn AJ, Saroha N, Tse ZTH. Contents, Followers, and Retweets of the Centers for Disease Control and Prevention’s Office of Advanced Molecular Detection (@CDC_AMD) Twitter Profile: Cross-Sectional Study. JMIR Public Health and Surveillance 2018;4(2):e33
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  39. Yuan X, Schuchard RJ, Crooks AT. Examining Emergent Communities and Social Bots Within the Polarized Online Vaccination Debate in Twitter. Social Media + Society 2019;5(3):205630511986546
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  40. Zheng H, Goh DH, Lee CS, Lee EWJ, Theng YL. Uncovering temporal differences in COVID‐19 tweets. Proceedings of the Association for Information Science and Technology 2020;57(1)
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  41. Wang B, Liu B, Zhang Q. An empirical study on Twitter’s use and crisis retweeting dynamics amid Covid-19. Natural Hazards 2021;107(3):2319
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  42. Garcia K, Berton L. Topic detection and sentiment analysis in Twitter content related to COVID-19 from Brazil and the USA. Applied Soft Computing 2021;101:107057
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  43. 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
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  44. Thelwall M, Thelwall S. A thematic analysis of highly retweeted early COVID-19 tweets: consensus, information, dissent and lockdown life. Aslib Journal of Information Management 2020;72(6):945
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  45. Lyu JC, Luli GK. 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
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  46. 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
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  47. Alnazzawi N, Fiorini N. Building a semantically annotated corpus for chronic disease complications using two document types. PLOS ONE 2021;16(3):e0247319
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  49. Jiang Y, Huang X, Li Z. Spatiotemporal Patterns of Human Mobility and Its Association with Land Use Types during COVID-19 in New York City. ISPRS International Journal of Geo-Information 2021;10(5):344
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  50. Kharlamov AA, Raskhodchikov AN, Pilgun M. Smart City Data Sensing during COVID-19: Public Reaction to Accelerating Digital Transformation. Sensors 2021;21(12):3965
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  51. Malik A, Antonino A, Khan ML, Nieminen M. Characterizing HIV discussions and engagement on Twitter. Health and Technology 2021;11(6):1237
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  52. Osakwe ZT, Cortés YI. Impact of COVID-19: A Text Mining Analysis of Twitter Data in Spanish Language. Hispanic Health Care International 2021;19(4):239
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  53. Bali AO, Halbusi HA, Ahmad AR, Lee KY, Lavorgna L. Public engagement in government officials’ posts on social media during coronavirus lockdown. PLOS ONE 2023;18(1):e0280889
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  54. 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
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  55. Joshi A, Miller C. Review of machine learning techniques for mosquito control in urban environments. Ecological Informatics 2021;61:101241
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  56. Xu WW, Tshimula JM, Dubé , Graham JE, Greyson D, MacDonald NE, Meyer SB. Unmasking the Twitter Discourses on Masks During the COVID-19 Pandemic: User Cluster–Based BERT Topic Modeling Approach. JMIR Infodemiology 2022;2(2):e41198
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  57. . Covid-19 Pandemisinin İlk Aylarında Twitter Gönderilerinin Metinsel Analizi.. Medical Research Reports 2022;5(3):136
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  58. Imran M, Qazi U, Ofli F. TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels. Data 2022;7(1):8
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  59. Ninkov A, Sedig K. A Framework for Online Public Health Debates: Some Design Elements for Visual Analytics Systems. Information 2022;13(4):201
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  60. Durazzi F, Müller M, Salathé M, Remondini D. Clusters of science and health related Twitter users become more isolated during the COVID-19 pandemic. Scientific Reports 2021;11(1)
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  61. Abdo MS, Alghonaim AS, Essam BA. Public perception of COVID-19’s global health crisis on Twitter until 14 weeks after the outbreak. Digital Scholarship in the Humanities 2021;36(3):509
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  62. Pilgun M, Koreneva Antonova O. Información implícita y explícita en la percepción del covid-19 en los medios de comunicación social en español, alemán y ruso. Palabra Clave 2022;25(1):1
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  63. Sano Y, Hori A, Kolahi J. 12-year observation of tweets about rubella in Japan: A retrospective infodemiology study. PLOS ONE 2023;18(5):e0285101
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  64. Finnegan A, Subburaj S, Hunter K, Parkash P, Shulman E, Ramkalawan J, Huchko MJ. Big Data, Machine Learning and Contraceptive Use: A Scoping Review. Oxford Open Digital Health 2023;1
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  65. Aizaz M, Khan F, Ali B, Ahmad S, Naseem K, Mishra S, Abbas FA, Yang G. Significance of Digital Health Technologies (DHTs) to manage communicable and non-communicable diseases in Low and Middle-Income Countries (LMICs). Health and Technology 2023;13(6):883
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  66. Pelletier A, Kaewkitipong L, Guitton MJ. Using technology to study refugee, conflict-affected, and hard-to-reach populations: Methodological and ethical considerations. Computers in Human Behavior 2024;152:108053
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  67. Ashayeri M, Abbasabadi N. Unraveling energy justice in NYC urban buildings through social media sentiment analysis and transformer deep learning. Energy and Buildings 2024;306:113914
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According to Crossref, the following books are citing this article (DOI 10.2196/publichealth.6925):

  1. Ahmed W, Bath PA, Sbaffi L, Demartini G. Social Computing and Social Media. Participation, User Experience, Consumer Experience, and Applications of Social Computing. 2020. Chapter 32:447
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  2. Sedkaoui S, Khelfaoui M, Keltoum O. International Conference on Managing Business Through Web Analytics. 2022. Chapter 28:395
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  3. Gilbert J, Niu J, de Montigny S, Ng V, Rees E. AI for Disease Surveillance and Pandemic Intelligence. 2022. Chapter 9:101
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  4. . Artificial Intelligence in Performance‐Driven Design. 2024. :159
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