Can tweets predict citations?

The October-December 2011 issue of the Journal of Medical Internet Research featured a very intriguing editorial under the title “Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact” [PMID 22173204].  In the article, Gunther Eysenbach attempted to analyze mentions of JMIR articles on Twitter within the first 30 days of their publication, and correlate that with eventual citations by other articles.  His conclusion: “Highly tweeted articles were 11 times more likely to be highly cited than less-tweeted articles… Top-cited articles can be predicted from top-tweeted articles with 93% specificity and 75% sensitivity… Tweets can predict highly cited articles within the first 3 days of article publication.”

The appearance of the article, however, showed another effect of social media on research: intense and immediate scrutiny of new research immediately upon publication.  Shortly after Eysenbach’s article appeared, bloggers like Phil Davis at Scholarly Kitchen began to raise questions about the article’s methods and its ethics.  Eysenbach is actually the editor of JMIR, and the fact that he chose his own journal as an outlet for his research struck some as suspicious, if not improper — especially since the article’s conflict-of-interest statement revealed that JMIR had registered the domain names twimpact.org, twimpactfactor.org and twimpactfactor.com to provide services tracking the phenomenon described by the article.  Since the articles whose “twimpact” was studied by the article appeared in JMIR, a certain number of the “twittations” were automatic ones by JMIR‘s own twitter account, and the article originally included a significant number of citations of JMIR articles — which some suspected as a way of artificially influencing JMIR‘s impact figures.

Eysenbach eventually issued a correction to his own article addressing some of these concerns — but the intrigue certainly emphasizes the need for additional, independent research on the part that social media conversation is beginning  to play in the larger scholarly communications ecosystem.

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