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

Data collected by social media platforms have recently been introduced as a new source for indicators to help measure the impact of scholarly research in ways that are complementary to traditional citation-based indicators. Data generated from social media activities related to scholarly content can be used to reflect broad types of impact. This paper aims to provide systematic evidence regarding how often Twitter is used to diffuse journal articles in the biomedical and life sciences. The analysis is based on a set of 1.4 million documents covered by both PubMed and Web of Science (WoS) and published between 2010 and 2012. The number of tweets containing links to these documents was analyzed to evaluate the degree to which certain journals, disciplines, and specialties were represented on Twitter. It is shown that, with less than 10% of PubMed articles mentioned on Twitter, its uptake is low in general. The relationship between tweets and WoS citations was examined for each document at the level of journals and specialties. The results show that tweeting behavior varies between journals and specialties and correlations between tweets and citations are low, implying that impact metrics based on tweets are different from those based on citations. A framework utilizing the coverage of articles and the correlation between Twitter mentions and citations is proposed to facilitate the evaluation of novel social-media based metrics and to shed light on the question in how far the number of tweets is a valid metric to measure research impact.Comment: 22 pages, 4 figures, 5 table

Social Media Attention Increases Article Visits: An Investigation on Article-Level Referral Data of PeerJ

In order to better understand the effect of social media in the dissemination of scholarly articles, employing the daily updated referral data of 110 PeerJ articles collected over a period of 345 days, we analyze the relationship between social media attention and article visitors directed by social media. Our results show that social media presence of PeerJ articles is high. About 68.18% of the papers receive at least one tweet from Twitter accounts other than @PeerJ, the official account of the journal. Social media attention increases the dissemination of scholarly articles. Altmetrics could not only act as the complement of traditional citation measures but also play an important role in increasing the article downloads and promoting the impacts of scholarly articles. There also exists a significant correlation among the online attention from different social media platforms. Articles with more Facebook shares tend to get more tweets. The temporal trends show that social attention comes immediately following publication but does not last long, so do the social media directed article views

COVID-19 publications: Database coverage, citations, readers, tweets, news, Facebook walls, Reddit posts

© 2020 The Authors. Published by MIT Press. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1162/qss_a_00066The COVID-19 pandemic requires a fast response from researchers to help address biological, medical and public health issues to minimize its impact. In this rapidly evolving context, scholars, professionals and the public may need to quickly identify important new studies. In response, this paper assesses the coverage of scholarly databases and impact indicators during 21 March to 18 April 2020. The rapidly increasing volume of research, is particularly accessible through Dimensions, and less through Scopus, the Web of Science, and PubMed. Google Scholar’s results included many false matches. A few COVID-19 papers from the 21,395 in Dimensions were already highly cited, with substantial news and social media attention. For this topic, in contrast to previous studies, there seems to be a high degree of convergence between articles shared in the social web and citation counts, at least in the short term. In particular, articles that are extensively tweeted on the day first indexed are likely to be highly read and relatively highly cited three weeks later. Researchers needing wide scope literature searches (rather than health focused PubMed or medRxiv searches) should start with Dimensions (or Google Scholar) and can use tweet and Mendeley reader counts as indicators of likely importance

Co-saved, co-tweeted, and co-cited networks

This is an accepted manuscript of an article published by Wiley-Blackwell in Journal of the Association for Information Science and Technology on 14/05/2018, available online: https://doi.org/10.1002/asi.24028 The accepted version of the publication may differ from the final published version.Counts of tweets and Mendeley user libraries have been proposed as altmetric alternatives to citation counts for the impact assessment of articles. Although both have been investigated to discover whether they correlate with article citations, it is not known whether users tend to tweet or save (in Mendeley) the same kinds of articles that they cite. In response, this article compares pairs of articles that are tweeted, saved to a Mendeley library, or cited by the same user, but possibly a different user for each source. The study analyzes 1,131,318 articles published in 2012, with minimum tweeted (10), saved to Mendeley (100), and cited (10) thresholds. The results show surprisingly minor overall overlaps between the three phenomena. The importance of journals for Twitter and the presence of many bots at different levels of activity suggest that this site has little value for impact altmetrics. The moderate differences between patterns of saving and citation suggest that Mendeley can be used for some types of impact assessments, but sensitivity is needed for underlying differences

Academics' online presence guidelines: A four step guide to taking control of your visibility

OpenUCT published Academics' online presence guidelines: A four step guide to taking control of your visibility in 2012

Do you cite what you tweet? Investigating the relationship between tweeting and citing research articles

The last decade of altmetrics research has demonstrated that altmetrics have a low to moderate correlation with citations, depending on the platform and the discipline, among other factors. Most past studies used academic works as their unit of analysis to determine whether the attention they received on Twitter was a good predictor of academic engagement. Our work revisits the relationship between tweets and citations where the tweet itself is the unit of analysis, and the question is to determine if, at the individual level, the act of tweeting an academic work can shed light on the likelihood of the act of citing that same work. We model this relationship by considering the research activity of the tweeter and its relationship to the tweeted work. Results show that tweeters are more likely to cite works affiliated with their same institution, works published in journals in which they also have published, and works in which they hold authorship. It finds that the older the academic age of a tweeter the less likely they are to cite what they tweet, though there is a positive relationship between citations and the number of works they have published and references they have accumulated over time