The differential impact of scientific quality, bibliometric factors, and social media activity on the influence of systematic reviews and meta-analyses about psoriasis

Abstract

Researchers are increasingly using on line social networks to promote their work. Some authors have suggested that measuring social media activity can predict the impact of a primary study (i.e., whether or not an article will be highly cited). However, the influence of variables such as scientific quality, research disclosures, and journal characteristics on systematic reviews and meta-analyses has not yet been assessed. The present study aims to describe the effect of complex interactions between bibliometric factors and social media activity on the impact of systematic reviews and meta-analyses about psoriasis (PROSPERO 2016: CRD42016053181). Methodological quality was assessed using the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) tool. Altmetrics, which consider Twitter, Facebook, and Google+ mention counts as well as Mendeley and SCOPUS readers, and corresponding article citation counts from Google Scholar were obtained for each article. Metadata and journal-related bibliometric indices were also obtained. One-hundred and sixty-four reviews with available altmetrics information were included in the final multifactorial analysis, which showed that social media and impact factor have less effect than Mendeley and SCOPUS readers on the number of cites that appear in Google Scholar. Although a journal’s impact factor predicted the number of tweets (OR, 1.202; 95% CI, 1.087–1.049), the years of publication and the number of Mendeley readers predicted the number of citations in Google Scholar (OR, 1.033; 95% CI, 1.018–1.329). Finally, methodological quality was related neither with bibliometric influence nor social media activity for systematic reviews. In conclusion, there seems to be a lack of connectivity between scientific quality, social media activity, and article usage, thus predicting scientific success based on these variables may be inappropriate in the particular case of systematic reviews.

If I tweet will you cite later? Follow-up on the effect of social media exposure on article downloads and citations

“…The same study found a low correlation (r = 0.12) between blog counts and traditional citations and a medium to large correlation between bookmark counts from online reference managers and citation counts (r = 0.23 for CiteULike and r = 0.51 for Mendeley). Online reference managers have been found to have stronger correlations with citations in other studies as well (Rosenkrantz et al 2017;Ruano et al 2018).…”

“…Moreover, qualitative analysis suggests that article topics discussed in SM are more likely to relate to the more controversial and emotive areas (Knight 2014). As a result, predicting scientific success based on SM activity may not be appropriate (Ruano et al 2018). Simple counting of online mentions without taking into account the content can lead to wrong conclusions, for instance in case of scientific misconduct that might receive a lot of SM attention (Bornmann and Haunschild 2018) or in case of automated software used for SM or single use tweets and duplicate tweets (Robinson-Garcia et al 2017).…”

An assessment of the quality of current clinical meta-analyses

“…While this finding is echoed in some studies, it is in opposition to others. Ruano et al recently evaluated quality of systematic reviews and MAs on psoriasis and found no association between quality and bibliometric factors [14]. However, Fleming et al reported in 2014 that systematic reviews published in higher impact journals were undertaken more rigorously (per impact factor unit: β = 0.68%; 95% CI 0.32-1.04; P < 0.001) [15].…”

The Relationship Between Institutional Factors, Citation and Altmetric Counts of Publications from Finnish Universities

“…However, they find that the coverage and overall number of mentions was very low for all studied platforms, with the possible exception of Twitter. More recently, some other studies have also found a connection between different altmetrics and later number of citations (e.g., Wang et al 2017;Finch, O'Hanlon, & Dudley, 2018;Costas, Zahedi & Wouters, 2015), while other studies have not found any connection (e.g., Hassan et al 2017;Delli et al 2017;O'Connor et al 2017;Ruano et al 2018). These findings may be a result of several factors including differences in methodology, data samples, or possibly changes in the usage of specific platforms over time.…”