Tweeting biomedicine: an analysis of tweets and citations in the biomedical literature (1308.1838v1)

Abstract: 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.

• The paper investigates Twitter as an alternative metric for research impact using a dataset of 1.4 million biomedical articles.
• The paper finds that fewer than 10% of articles are mentioned on Twitter, with an average of 2.5 tweets per mentioned article.
• The paper highlights a weak correlation (Spearman 0.183) between tweets and citations, suggesting that tweet counts reflect different facets of research engagement.

Analyzing Twitter's Role in Biomedical Research Dissemination

The paper "Tweeting biomedicine: an analysis of tweets and citations in the biomedical literature" investigates the intersection of social media activity, specifically Twitter, and the academic dissemination of biomedical research. With the backdrop of growing altmetrics, the paper explores the degree to which Twitter can serve as an alternative indicator of research impact. Utilizing a dataset of 1.4 million articles from both PubMed and Web of Science (WoS), published between 2010 and 2012, the authors aim to quantify and characterize the presence of biomedical literature on Twitter.

The paper unfolds in three main inquiries: the coverage of biomedical papers on Twitter, the impact and frequency of tweets, and the comparison between tweet counts and traditional citation metrics. Under these umbrellas, the findings demonstrate a relatively limited uptake of Twitter for disseminating scientific articles, with less than 10% of the articles being mentioned on the platform. While Twitter coverage increased over time, with over 20% of articles from 2012 receiving at least one mention, articles are generally mentioned sparingly, averaging 2.5 tweets per mentioned document.

A more granular analysis reveals significant variation across journals, disciplines, and specialties. Journals such as Nature and prestigious medical journals like the New England Journal of Medicine receive higher Twitter coverage and citation rates. On a broader level, fields such as General & Internal Medicine and Experimental Psychology stand out with relatively higher Twitter citation activity.

However, the paper highlights weak correlations between Twitter metrics and traditional citations, with a Spearman correlation of only 0.183. This suggests that tweets do not parallel citation behavior and might instead capture different facets of research impact, potentially reflecting broader public interest or engagement rather than academic influence.

The implications of the paper are multifaceted. Practically, the findings indicate that while Twitter holds potential as a platform for science communication, its use as a metric for scholarly impact is not straightforward. Given the low correlation with traditional citations, tweets may better reflect public engagement rather than the academic influence of a publication.

Theoretically, this prompts a need to further explore altmetrics and their role within scholarly communication. The paper advocates caution in integrating tweet counts as measures of research impact without a deeper understanding of the motivations and contexts in which articles are tweeted. Consequently, future endeavors should focus on a nuanced understanding of altmetric indicators, considering the ecosystem of actors, motivations, and scientific conversations on networks like Twitter.

The paper's methodological rigor and reliance on a large dataset contribute to a substantive baseline paper of Twitter's role in biomedical research dissemination. However, it also opens avenues for further explorative research, including qualitative studies on the motivations behind scholarly tweeting and its broader impact on science communication.

In conclusion, while Twitter may offer valuable insights into the engagement with and dissemination of biomedical research, its validity as a solitary metric for assessing research impact remains limited. The work calls for a holistic approach to altmetrics, considering the diverse and multifaceted nature of scholarly and public engagement with scientific literature.