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

Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1013) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1570) Infodemiology and Infoveillance (1274) Mass Media/Social Media Communication and Campaigns (448) HIV/AIDS/STI Prevention and Care (819)

Published on in Vol 4, No 4 (2018): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10262, first published .
How Twitter Can Support the HIV/AIDS Response to Achieve the 2030 Eradication Goal: In-Depth Thematic Analysis of World AIDS Day Tweets

How Twitter Can Support the HIV/AIDS Response to Achieve the 2030 Eradication Goal: In-Depth Thematic Analysis of World AIDS Day Tweets

How Twitter Can Support the HIV/AIDS Response to Achieve the 2030 Eradication Goal: In-Depth Thematic Analysis of World AIDS Day Tweets

Authors of this article:

Michelle Odlum1 Author Orcid Image ;   Sunmoo Yoon1 Author Orcid Image ;   Peter Broadwell2 Author Orcid Image ;   Russell Brewer3 Author Orcid Image ;   Da Kuang4 Author Orcid Image
Article Authors Cited by (12) Tweetations (17) Metrics

Journals

  1. Mavragani A, Ochoa G. Google Trends in Infodemiology and Infoveillance: Methodology Framework. JMIR Public Health and Surveillance 2019;5(2):e13439 View
  2. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
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  4. Abbasi-Perez A, Alvarez-Mon M, Donat-Vargas C, Ortega M, Monserrat J, Perez-Gomez A, Sanz I, Alvarez-Mon M. Analysis of Tweets Containing Information Related to Rheumatological Diseases on Twitter. International Journal of Environmental Research and Public Health 2021;18(17):9094 View
  5. Delir Haghighi P, Burstein F, Urquhart D, Cicuttini F. Investigating Individuals’ Perceptions Regarding the Context Around the Low Back Pain Experience: Topic Modeling Analysis of Twitter Data. Journal of Medical Internet Research 2021;23(12):e26093 View
  6. 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
  7. Burgess R, Feliciano J, Lizbinski L, Ransome Y. Trends and Characteristics of #HIVPrevention Tweets Posted Between 2014 and 2019: Retrospective Infodemiology Study. JMIR Public Health and Surveillance 2022;8(8):e35937 View
  8. Déguilhem A, Malaab J, Talmatkadi M, Renner S, Foulquié P, Fagherazzi G, Loussikian P, Marty T, Mebarki A, Texier N, Schuck S. Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media. JMIR Infodemiology 2022;2(2):e39849 View
  9. Sharma R, Bharathy G, Karimi F, Mishra A, Prasad M. Thematic Analysis of Big Data in Financial Institutions Using NLP Techniques with a Cloud Computing Perspective: A Systematic Literature Review. Information 2023;14(10):577 View
  10. Wu D, Ng M, Gupta S, Raynor P, Tao Y, Ren Y, Li X, Olatosi B, Hung P, Qiao S, Zhang J, Fillo J, Guille C, Eichelberger K. Disclosure Patterns of Opioid Use Disorders in Perinatal Care During the Opioid Epidemic on X from 2019 to 2021: Thematic Analysis (Preprint). JMIR Pediatrics and Parenting 2023 View
  11. Mageshwari V, Aroquiaraj I. A novel technique for identification and classification of HIV/AIDS related social media data using LD-KMEANS and DBN-LSTM. Multimedia Tools and Applications 2024 View
  12. Gamayo G, Santos Y, Tanchuan V, Villacastin J. Unearthing the disabling perplexities of a Filipino PLHIV online community on X’s #PLHIVDiaries as socially shared inquiry fostering pakikipagkapwa. Journal of Asian Pacific Communication 2024 View