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Social Network Representation and Dissemination of Pre-Exposure Prophylaxis (PrEP): A Semantic Network Analysis of HIV Prevention Drug on Twitter

  • Zheng An
  • Margaret McLaughlin
  • Jinghui Hou
  • Yujung Nam
  • Chih-Wei Hu
  • Mina Park
  • Jingbo Meng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8531)

Abstract

Daily oral pre-exposure prophylaxis (PrEP) is a new approach to HIV prevention. The study aims to examine how PrEP has been represented and disseminated on one of the most popular social networking sites - Twitter. We collected 1435 public tweets containing the word “Truvada.” After computer-mediated and manual de-duplication, we analyzed 447 unique tweets and calculated weights between two words to measure their co-occurrence in 7-word windows. Semantic networks of PrEP-related tweets were constructed. We found that Twitter was used to generate public discussions and collectively interpret new medical information, especially in frequently propagated tweets and from users with more followers. In the meantime, the results revealed the presence of illicit online pharmacies that marketed and sold PrEP without the need for a prescription. We discussed implications for public health and made urgent call for better regulation of online pharmacies.

Keywords

PrEP HIV Twitter Semantic Network Illicit Online Pharmacies 

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References

  1. 1.
    Chou, W.Y.S., Hunt, Y.M., Beckjord, E.B., Moser, R.P., Hesse, B.W.: Social media use in the United States: implications for health communication. Journal of Medical Internet Research 11(4) (2009) Clarke, J. N. (1992)Google Scholar
  2. 2.
    Fox, S., Duggan, M.: Health online 2013. Pew Internet Project (2013), http://pewinternet.org/Reports/2013/Health-online.aspx (retrieved)
  3. 3.
    Vance, K., Howe, W., Dellavalle, R.P.: Social Internet sites as a source of public health information. Dermatologic Clinics 27(2), 133–136 (2009)Google Scholar
  4. 4.
    CNN. Patients use Facebook, Twitter, to get health information (2011), http://thechart.blogs.cnn.com/2011/03/04/patients-use-facebook-twitter-to-get-health-information/ (retrieved)
  5. 5.
    Love, B., Himelboim, I., Holton, A., Stewart, K.: Twitter as a source of vaccination information: Content drivers and what they are saying. American Journal of Infection Control 41(6), 568–570 (2013)CrossRefGoogle Scholar
  6. 6.
    Robillard, J.M., Johnson, T.W., Hennessey, C., Beattie, B.L., Illes, J.: Aging 2.0: Health Information about Dementia on Twitter. PloS One 8(7), e69861 (2013)Google Scholar
  7. 7.
    Scanfeld, D., Scanfeld, V., Larson, E.: Dissemination of health information through social networks: Twitter and antibiotics. American Journal of Infection Control 38(3), 182–188 (2010)CrossRefGoogle Scholar
  8. 8.
    McLaughlin, M.L., Hou, J., Park, M., Hu, C., Meng, J.: Dissemination of Truvada-related health information through Twitter. In: American Public Health Association, 141st Annual Meeting (2013)Google Scholar
  9. 9.
    Mackey, T.K., Liang, B.A.: Global Reach of Direct-to-Consumer Advertising Using Social Media for Illicit Online Drug Sales. Journal of Medical Internet Research 15(5) (2013)Google Scholar
  10. 10.
    Hanson, C.L., Burton, S.H., Giraud-Carrier, C., West, J.H., Barnes, M.D., Hansen, B.: Tweaking and tweeting: exploring Twitter for nonmedical use of a psychostimulant drug (Adderall) among college students. Journal of Medical Internet Research 15(4), e62 (2013)Google Scholar
  11. 11.
    Kemp, C.: Mid-term Prescription Drug Abuse: Does Social Media Play a Role? (2012), http://cathykemp.blogspot.com/2012/03/mid-term-prescription-drug-abuse-does.html (retrieved)
  12. 12.
    Liang, B.A., Mackey, T.K.: Prevalence and global health implications of social media in direct-to-consumer drug advertising. Journal of Medical Internet Research 13(3) (2011)Google Scholar
  13. 13.
    National Center on Addiction and Substance Abuse. “You’ve got drugs!” V: Prescritipon drug pushers on the Internet (2008), http://www.casacolumbia.org/addiction-research/reports/youve-got-drugs-perscription-drug-pushers-internet-2008 (retrieved)
  14. 14.
    FDA. FDA takes action to protect consumers from dangerous medicines sold by illegal online pharmacies (2013a), http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm358794.htm (retrieved)
  15. 15.
  16. 16.
    DuPont, R.: Prescription Drug Abuse: An Epidemic Dilemma. Journal of Psychoactive Drugs, 127–132 (June 2010)Google Scholar
  17. 17.
    CDC. Vital signs: Overdoses of prescription opioid pain relievers and other drugs among women – United States, 1999-2010 (2013), http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6226a3.htm (retrieved)
  18. 18.
    Mackey, T.K., Liang, B.A., Strathdee, S.A.: Digital social media, youth, and nonmedical use of prescription drugs: the need for reform. Journal of Medical Internet Research 15(7), e143 (2013)Google Scholar
  19. 19.
    Jena, A.A.: Growing Internet Use May Help Explain the Rise in Prescription Drug Abuse in the United States. Health Affairs, 1192–1199 (June 2011)Google Scholar
  20. 20.
    Guo, L.: The Application of Social Network Analysis in Agenda Setting Research: A Methodological Exploration. Journal of Broadcasting & Electronic Media 56(4), 616–631 (2012)CrossRefGoogle Scholar
  21. 21.
    Ognyanova, K., Monge, P.: A Multitheoretical, Multilevel, Multidimensional Network Model of the Media System. Communication Yearbook 37, 67 (2013)Google Scholar
  22. 22.
    Schultz, F., Kleinnijenhuis, J., Oegema, D., Utz, S., van Atteveldt, W.: Strategic framing in the BP crisis: A semantic network analysis of associative frames. Public Relations Review 38, 97–107 (2012)CrossRefGoogle Scholar
  23. 23.
    Kitchin, R.M.: Cognitive maps: What are they and they study them? Journal of Environemntal Psychology 14(1), 1–19 (1994); McCombs, M.E., Shaw, D.L.: The agenda-setting function of the mass media. Public Opinion Quarterly 36, 176–187 (1972)Google Scholar
  24. 24.
    Clarke, J.N.: Cancer, heart disease, and AIDS: What do the media tell us about these diseases? Health Communication 4, 105–120 (1992)CrossRefGoogle Scholar
  25. 25.
    Tian, Y., Stewart, C.: Framing the SARS crisis: A computer-assisted text analysis of CNN and BBC online news reports of SARS. Asian Journal of Communication 15(3), 289–301 (2005)CrossRefGoogle Scholar
  26. 26.
    Murphy, P.: Framing the nicotine debate: A cultural approach to risk. Health Communication 13(2), 119–140 (2001)Google Scholar
  27. 27.
    Katz, M.H.: Pre-exposure prophylaxis for HIV: Can it be implemented in the real world? American Journal of Preventive Medicine 44(1), S161–S162 (2013)Google Scholar
  28. 28.
    Gilead Sciences Inc. Medication guide Truvada (2013), http://www.gilead.com/~/media/Files/pdfs/medicines/hiv/truvada/truvada_medication_guide.pdf (retrieved)
  29. 29.
    Cha, M., Haddadi, H., Benevenuto, F., Gummadi, P.K.: Measuring User Influence in Twitter: The Million Follower Fallacy. In: ICWSM, vol. 10, pp. 10–17 (2010)Google Scholar
  30. 30.
    Westerman, D., Spence, P.R., Van Der Heide, B.: A social network as information: The effect of system generated reports of connectedness on credibility on Twitter. Computers in Human Behavior 28(1), 199–206 (2012)CrossRefGoogle Scholar
  31. 31.
    Ryan Haight Online Pharmacy Consumer Protection Act of 2008 (2008), https://www.govtrack.us/congress/bills/110/hr6353/text (retrieved)
  32. 32.
    Suh, B., Hong, L., Pirolli, P., Chi, E.H.: Want to be retweeted? Large scale analytics on factors impacting retweet in twitter network. In: 2010 IEEE Second International Conference on Social Computing (SocialCom), pp. 177–184. IEEE (August 2010)Google Scholar
  33. 33.
    Eysenbach, G.: Online Prescribing of Sildanefil (Viagra [R]) on the World Wide Web. Journal of Medical Internet Research 1(2), e10 (1999)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Zheng An
    • 1
  • Margaret McLaughlin
    • 1
  • Jinghui Hou
    • 1
  • Yujung Nam
    • 1
  • Chih-Wei Hu
    • 1
  • Mina Park
    • 1
  • Jingbo Meng
    • 1
  1. 1.University of Southern CaliforniaLos AngelesUSA

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