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Hashtag Peer-Review: Does Early Social Media Success Correlate with Conventional Metrics of Publication Impact?

Login to Access Video or Poster Abstract: MP69-07
Sources of Funding: None

Introduction

Social media is increasingly utilized as a means to disseminate information, including scientific study. In contrast to the conventional academic peer-review process, social media may serve as an efficient vehicle to both vet and widely broadcast research. To test this hypothesis, we evaluated whether Twitter activity at a national urology meeting mirrors subsequent journal impact factor (IF), a traditional measure of academic impact._x000D_

Methods

We retrospectively reviewed historical Twitter data obtained through the Keyhole archiving platform using the hashtag “#aua15” between May 1 and June 1, 2015 reflecting the widely utilized hashtag of the 2015 American Urological Association (AUA) meeting. We analyzed all tweets receiving ? 4 likes/retweets (RT). Among tweets reporting on newly presented studies with discernable attribution, we evaluated subsequent publication status within 18 months, including IF. Published studies with multiple tweets were grouped, and RTs were summed. We assessed the relationship between social media reception (likes/RT) and subsequent journal IF using Pearson’s correlation.

Results

A total of 15,303 posts were associated with “#aua15” drawing from 2,015 users, reaching 2,263,438 unique twitter users, and culminated in 27,327,075 impressions (number of times users have seen posts containing “#aua15”). 451 of the most promoted tweets were analyzed, including 74 related to discernable data with author attribution. The most common categories of tweets included references to data or studies without discrete author or study attribution (18.8%), generalized comments (17.5%), and meeting-related announcements (16.6%). At 18 months following the AUA, 44 studies were identifiable on PubMed (59%). Among published studies there was a modest, positive correlation between number of likes/RT and IF (r=0.59)._x000D_

Conclusions

Measures of social media engagement with data presented at a national medical meeting positively correlated with subsequent publication impact factor within 18 months of presentation. _x000D_ _x000D_

Funding

None

Authors
Kevin Nguyen
Cary Gross
Matthew Cooperberg
Matthew Katz
Adam Hittelman
Jamil Syed
Peter Schulam
Michael Leapman
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