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Desai T, Dhingra V, Shariff A, et al. Quantifying the Twitter Influence of Third Party Commercial Entities versus Healthcare Providers in Thirteen Medical Conferences from 2011 - 2013. PLoS One. 2016;11(9):e0162376doi: 10.1371/journal.pone.0162376.
Desai, T., Dhingra, V., Shariff, A., Shariff, A., Lerma, E., Singla, P., Kachare, S., Syed, Z., Minhas, D., Madanick, R., & Fang, X. (2016). Quantifying the Twitter Influence of Third Party Commercial Entities versus Healthcare Providers in Thirteen Medical Conferences from 2011 - 2013. PloS one, 11(9), e0162376. https://doi.org/10.1371/journal.pone.0162376
Desai, Tejas, et al. "Quantifying the Twitter Influence of Third Party Commercial Entities versus Healthcare Providers in Thirteen Medical Conferences from 2011 - 2013." PloS one vol. 11,9 (2016): e0162376. doi: https://doi.org/10.1371/journal.pone.0162376
Desai T, Dhingra V, Shariff A, Shariff A, Lerma E, Singla P, Kachare S, Syed Z, Minhas D, Madanick R, Fang X. Quantifying the Twitter Influence of Third Party Commercial Entities versus Healthcare Providers in Thirteen Medical Conferences from 2011 - 2013. PLoS One. 2016 Sep 26;11(9):e0162376. doi: 10.1371/journal.pone.0162376. eCollection 2016. PMID: 27668433; PMCID: PMC5036883.
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PLoS One. 2016 Sep 26;11(9):e0162376. doi: 10.1371/journal.pone.0162376. eCollection 2016.

Quantifying the Twitter Influence of Third Party Commercial Entities versus Healthcare Providers in Thirteen Medical Conferences from 2011 - 2013.

PloS one

Tejas Desai, Vibhu Dhingra, Afreen Shariff, Aabid Shariff, Edgar Lerma, Parteek Singla, Swapnil Kachare, Zoheb Syed, Deeba Minhas, Ryan Madanick, Xiangming Fang

Affiliations

  1. Division of Nephrology, W.G. (Bill) VA Medical Center, Salisbury, North Carolina, United States of America.
  2. NOD Analytics, Charlotte, North Carolina, United States of America.
  3. Department of Internal Medicine, East Carolina University - Brody School of Medicine, Greenville, North Carolina, United States of America.
  4. Division of Endocrinology, Duke University, Durham, North Carolina, USA.
  5. Monsanto Company, Raleigh, North Carolina, United States of America.
  6. Division of Nephrology, University of Illinois at Chicago College of Medicine, Chicago, Illinois, United States of America.
  7. Department of Internal Medicine, Barnes Jewish Hospital, St. Louis, Missouri, United States of America.
  8. Department of Surgery, East Carolina University - Brody School of Medicine, Greenville, North Carolina, United States of America.
  9. College of Arts and Sciences, College of William and Mary, Yorktown, Virginia, United States of America.
  10. Division of Rheumatology, Cedars-Sinai Medical Center, Los Angeles, California, United States of America.
  11. Division of Gastroenterology, University of North Carolina, Chapel Hill, North Carolina, United States of America.
  12. Department of Biostatistics, East Carolina University - Brody School of Medicine, Greenville, North Carolina, United States of America.

PMID: 27668433 PMCID: PMC5036883 DOI: 10.1371/journal.pone.0162376

Abstract

INTRODUCTION: Twitter channels are increasingly popular at medical conferences. Many groups, including healthcare providers and third party entities (e.g., pharmaceutical or medical device companies) use these channels to communicate with one another. These channels are unregulated and can allow third party commercial entities to exert an equal or greater amount of Twitter influence than healthcare providers. Third parties can use this influence to promote their products or services instead of sharing unbiased, evidence-based information. In this investigation we quantified the Twitter influence that third party commercial entities had in 13 major medical conferences.

METHODS: We analyzed tweets contained in the official Twitter hashtags of thirteen medical conferences from 2011 to 2013. We placed tweet authors into one of four categories based on their account profile: healthcare provider, third party commercial entity, none of the above and unknown. We measured Twitter activity by the number of tweet authors per category and the tweet-to-author ratio by category. We measured Twitter influence by the PageRank of tweet authors by category.

RESULTS: We analyzed 51159 tweets authored by 8778 Twitter account holders in 13 conferences that were sponsored by 5 medical societies. A quarter of all authors identified themselves as healthcare providers, while only 18% could be identified as third party commercial entities. Healthcare providers had a greater tweet-to-author ratio than their third party commercial entity counterparts (8.98 versus 6.93 tweets). Despite having less authors and composing less tweets, third party commercial entities had a statistically similar PageRank as healthcare providers (0.761 versus 0.797).

CONCLUSION: The Twitter influence of third party commercial entities (PageRank) is similar to that of healthcare providers. This finding is interesting because the number of tweets and third party commercial entity authors required to achieve this PageRank is far fewer than that needed by healthcare providers. Without safety mechanisms in place, the Twitter channels of medical conferences can devolve into a venue for the spread of biased information rather than evidence-based medical knowledge that is expected at live conferences. Continuing to measure the Twitter influence that third parties exert can help conference organizers develop reasonable guidelines for Twitter channel activity.

Conflict of interest statement

TD is an employee of the United States Government. TD is the creator of Nephrology On-Demand. This affiliation does not alter our adherence to PLOS ONE policies on sharing data and materials. Aabid Sh

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