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Citing this Article

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Published on 19.06.17 in Vol 3, No 2 (2017): Apr-Jun

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

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

According to Crossref, the following articles are citing this article (DOI 10.2196/publichealth.7157):

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

  1. 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
    CrossRef
  2. Saura JR, Palos-Sanchez P, Grilo A. Detecting Indicators for Startup Business Success: Sentiment Analysis Using Text Data Mining. Sustainability 2019;11(3):917
    CrossRef
  3. 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)
    CrossRef
  4. 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
    CrossRef
  5. 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
    CrossRef
  6. Wang SV, Patterson OV, Gagne JJ, Brown JS, 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;
    CrossRef
  7. Deiner MS, Fathy C, Kim J, Niemeyer K, Ramirez D, Ackley SF, Liu F, Lietman TM, Porco TC. Facebook and Twitter vaccine sentiment in response to measles outbreaks. Health Informatics Journal 2019;25(3):1116
    CrossRef
  8. 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
    CrossRef
  9. 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 2019;
    CrossRef
  10. 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
    CrossRef
  11. 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
    CrossRef
  12. 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 2019;
    CrossRef
  13. Jia S. Leisure Motivation and Satisfaction: A Text Mining of Yoga Centres, Yoga Consumers, and Their Interactions. Sustainability 2018;10(12):4458
    CrossRef
  14. Park H, Jung H, On J, Park SK, Kang H. Digital Epidemiology: Use of Digital Data Collected for Non-epidemiological Purposes in Epidemiological Studies. Healthcare Informatics Research 2018;24(4):253
    CrossRef
  15. 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
    CrossRef
  16. 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
    CrossRef
  17. Chen T, Dredze M. Vaccine Images on Twitter: Analysis of What Images are Shared. Journal of Medical Internet Research 2018;20(4):e130
    CrossRef
  18. 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;
    CrossRef
  19. Gianfredi V, Bragazzi NL, 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
    CrossRef
  20. 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)
    CrossRef
  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;
    CrossRef
  22. Paul MJ, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/publichealth.7157)

:
  1. Kho SJ, Padhee S, Bajaj G, Thirunarayan K, Sheth A. Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining. 2019. Chapter 9:233
    CrossRef
  2. Sheth A, Purohit H, Smith GA, Brunn J, Jadhav A, Kapanipathi P, Lu C, Wang W. Encyclopedia of Social Network Analysis and Mining. 2018. Chapter 345:3212
    CrossRef
  3. Sheth A, Purohit H, Smith GA, Brunn J, Jadhav A, Kapanipathi P, Lu C, Wang W. Encyclopedia of Social Network Analysis and Mining. 2017. Chapter 345-1:1
    CrossRef