Tweeting biomedicine: An analysis of tweets and citations in the biomedical literature

Abstract

Data collected by social media platforms have been introduced as new sources for indicators to help measure the impact of scholarly research in ways that are complementary to traditional citation analysis. Data generated from social media activities can be used to reflect broad types of impact. This article aims to provide systematic evidence about how often Twitter is used to disseminate information about journal articles in the biomedical sciences. The analysis is based on 1.4 million documents covered by both PubMed and Web of Science and published between 2010 and 2012. The number of tweets containing links to these documents was analyzed and compared to citations to evaluate the degree to which certain journals, disciplines, and specialties were represented on Twitter and how far tweets correlate with citation impact. With less than 10% of PubMed articles mentioned on Twitter, its uptake is low in general but differs between journals and specialties. Correlations between tweets and citations are low, implying that impact metrics based on tweets are different from those based on citations. A framework using the coverage of articles and the correlation between Twitter mentions and citations is proposed to facilitate the evaluation of novel social-media-based metrics.

Can alternative indicators overcome language biases in citation counts? A comparison of Spanish and UK research

“…Previous studies have found lower Twitter coverage: 21% of about a million WoS journal articles published in 2012 (Haustein et al 2015), 20% of PubMed/WoS articles published in 2012 (Haustein et al 2014) and 13% of over half a million WoS publications published in (Costas et al 2015a) received one or more Twitter mentions. This suggests that more articles are now tweeted or that data collection by Altmetric.com is more comprehensive.…”

“…For instance, citations need time to accrue and citation time windows vary across disciplines (Wang 2013) and the longer time periods, the better for assessing the commercial benefit of scientific publications based on patent citations . In contrast, recent publications tend to attract more Twitter mentions than older publications (Haustein et al 2014). For recent years, older articles tend to attract more Mendeley readers (Thelwall and Sud 2015) but nothing is known about Wikipedia citations over time.…”

“…There is also evidence that a considerable number of Twitter mentions occur shortly after research is published (Eysenbach 2011; Priem and Costello 2010) and they seem to reflect attention, popularity or visibility rather than impact, so that Twitter mentions may be an early indicator of the level of attention (including publicity) that articles attract (Haustein et al 2014).…”

“…2 Nevertheless, the alternative indicators also have their own biases and limitations (Bornmann 2014;Holmberg 2015). For instance, the majority of altmetric sources have a low coverage of academic publications and some social media indicators seem to be only valuable for the most recent publications (Costas et al 2015a;Haustein et al 2014). The main drawback of indicators based on social media is perhaps their susceptibility for gaming (Jamali et al 2016;Wouters et al 2015).…”

“…Several studies have suggested that altmetrics complement citations rather than being alternatives (Haustein et al 2014). Moreover, altmetrics are less useful in fields with very low altmetric scores, including mathematics, computer science, and natural science and engineering (Costas et al 2015a).…”