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

Overview of attention for article published in PLoS ONE, January 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

twitter
48 tweeters
facebook
1 Facebook page

Citations

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5 Dimensions

Readers on

mendeley
13 Mendeley
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1 CiteULike
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Title
Quantifying the Twitter Influence of Third Party Commercial Entities versus Healthcare Providers in Thirteen Medical Conferences from 2011 – 2013
Published in
PLoS ONE, January 2016
DOI 10.1371/journal.pone.0162376
Pubmed ID
Authors

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

Abstract

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. 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. 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). 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.

Twitter Demographics

The data shown below were collected from the profiles of 48 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 15%
Unknown 11 85%

Demographic breakdown

Readers by professional status Count As %
Other 3 23%
Student > Master 3 23%
Student > Ph. D. Student 1 8%
Professor 1 8%
Lecturer 1 8%
Other 4 31%
Readers by discipline Count As %
Medicine and Dentistry 5 38%
Business, Management and Accounting 2 15%
Social Sciences 2 15%
Decision Sciences 1 8%
Nursing and Health Professions 1 8%
Other 2 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 28. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 August 2018.
All research outputs
#479,859
of 12,109,122 outputs
Outputs from PLoS ONE
#9,268
of 133,245 outputs
Outputs of similar age
#19,680
of 261,641 outputs
Outputs of similar age from PLoS ONE
#261
of 4,071 outputs
Altmetric has tracked 12,109,122 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 133,245 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 261,641 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 4,071 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.