Do Mendeley reader counts indicate the value of arts and humanities research?

Self Cite

Altmetrics are web‐based quantitative impact or attention indicators for academic articles that have been proposed to supplement citation counts. This article reports the first assessment of the extent to which mature altmetrics from http://altmetric.com and Mendeley associate with individual article quality scores. It exploits expert norm‐referenced peer review scores from the UK Research Excellence Framework 2021 for 67,030+ journal articles in all fields 2014–2017/2018, split into 34 broadly field‐based Units of Assessment (UoAs). Altmetrics correlated more strongly with research quality than previously found, although less strongly than raw and field normalized Scopus citation counts. Surprisingly, field normalizing citation counts can reduce their strength as a quality indicator for articles in a single field. For most UoAs, Mendeley reader counts are the best altmetric (e.g., three Spearman correlations with quality scores above 0.5), tweet counts are also a moderate strength indicator in eight UoAs (Spearman correlations with quality scores above 0.3), ahead of news (eight correlations above 0.3, but generally weaker), blogs (five correlations above 0.3), and Facebook (three correlations above 0.3) citations, at least in the United Kingdom. In general, altmetrics are the strongest indicators of research quality in the health and physical sciences and weakest in the arts and humanities.

Section: Discussionmentioning

confidence: 83%

Section: Resultsmentioning

confidence: 99%

Do altmetric scores reflect article quality? Evidence from the UK Research Excellence Framework 2021

Thelwall

Kousha

Abdoli

et al. 2023

Self Cite

“…Another topic of research examines the different metric systems that not only measure publications and citations but sometimes also user activity within the tool (Ovadia, 2014). Reading activity monitored in platforms such as Mendeley can, for example, provide good early impact evidence as this metrics appear before citations and correlate with citations in the long term (Thelwall, 2019). Sharing research data also becomes part of this metric when data, such as publications, are given unique DOIs and can be cited.…”

Section: Open Research Data Repositoriesmentioning

confidence: 99%

Open research data repositories: Practices, norms, and metadata for sharing images

Hansson

Dahlgren

2021

Open research data repositories are promoted as one of the cornerstones in the open research paradigm, promoting collaboration, interoperability, and largescale sharing and reuse. There is, however, a lack of research investigating what these sharing platforms actually share and a more critical interface analysis of the norms and practices embedded in this datafication of academic practice is needed. This article takes image data sharing in the humanities as a case study for investigating the possibilities and constraints in 5 open research data repositories. By analyzing the visual and textual content of the interface along with the technical means for metadata, the study shows how the platforms are differentiated in terms of signifiers of research paradigms, but that beneath the rhetoric of the interface, they are designed in a similar way, which does not correspond well with the image researchers' need for detailed metadata. Combined with the problem of copyright limitations, these data-sharing tools are simply not sophisticated enough when it comes to sharing and reusing images. The result also corresponds with previous research showing that these tools are used not so much for sharing research data, but more for promoting researcher personas.

How fast do scholarly papers get read by various user groups? A longitudinal and cross‐disciplinary analysis of the evolution of Mendeley readership

Fang,

Ho,

Han

et al. 2024

To provide a dynamic perspective on the evolution of Mendeley readership, this study conducts an 8‐year longitudinal analysis of approximately 3.4 million scholarly papers published in 2015. Mendeley readership data were collected annually from 2016 to 2023 for the sampled papers to analyze the temporal accumulation patterns of readership following publication. The results indicate that Mendeley readership exhibits a speed advantage compared to citations and a prevalence advantage compared to Twitter mentions, demonstrating both initial prevalence and sustained growth on a yearly basis. However, the patterns of accumulation vary across disciplines, with papers in Biomedical and Health Sciences showing the fastest accrual of extensive Mendeley readership data. Leveraging demographic data provided by Mendeley, this study further investigates how different user groups—categorized by academic status, disciplinary affiliation, and geographic location—engage with papers across various disciplines. The findings highlight Mendeley readership as a rapid and substantial altmetric, yet they also emphasize the need to interpret the nature of the attention captured by Mendeley readership with caution, considering its potential biases introduced by the varying engagement levels of different user groups across disciplines.