Bandingkan metode

	Mendeley Readership Analysis	Usage Bibliometrics (Downloads and COUNTER)
Bidang	Bibliometrika	Bibliometrika
Keluarga	Process / pipeline	Process / pipeline
Tahun asal	2014	2009
Pencetus	Ehsan Mohammadi & Mike Thelwall	Johan Bollen, Herbert Van de Sompel & colleagues (MESUR project)
Tipe	Altmetric pipeline using reference-manager readership counts	Usage-log pipeline for impact metrics from downloads and views
Sumber perintis	Mohammadi, E., & Thelwall, M. (2014). Mendeley readership altmetrics for the social sciences and humanities: Research evaluation and knowledge flows. Journal of the Association for Information Science and Technology, 65(8), 1627-1638.	Bollen, J., Van de Sompel, H., Hagberg, A., & Chute, R. (2009). A Principal Component Analysis of 39 Scientific Impact Measures. PLoS ONE, 4(6), e6022.
Alias	Reader Count Analysis, Mendeley Reader Metrics, Readership Altmetrics, Reference Manager Bookmarking Analysis	Download Metrics, Usage Factor Analysis, Usage-Based Impact Metrics, COUNTER Usage Analysis
Terkait	3	3
Ringkasan	Mendeley readership analysis uses the number of users who have saved an article to their personal library in the Mendeley reference manager as an indicator of scholarly attention. Ehsan Mohammadi and Mike Thelwall showed in 2014 that these reader counts have broad coverage, correlate moderately with later citations, and, because saving precedes citing, become available much earlier than citation data. Mendeley also exposes coarse demographic categories for its readers, such as students, researchers, and professionals, allowing analysis of who is engaging with research, including non-citing audiences in the social sciences and humanities. As one of the most studied altmetric sources, Mendeley readership offers an early and relatively well-covered signal that complements citations, while raising distinct questions about what saving a paper actually means.	Usage bibliometrics measures the impact of scholarly works from how often they are downloaded and viewed rather than how often they are cited. Drawing on server and publisher logs standardized through the COUNTER code of practice, it turns raw access events into impact indicators such as the usage factor. The MESUR project led by Johan Bollen and Herbert Van de Sompel was pivotal: their 2008 work demonstrated usage-based impact metrics built from large-scale usage logs, and their 2009 principal component analysis of thirty-nine impact measures showed that scientific impact is multidimensional, with usage metrics occupying a distinct region of the space from citation metrics. Usage signals accrue almost immediately and reflect a far larger readership than the subset of authors who eventually cite, making them an early and broad complement to citation analysis, provided the logs are carefully standardized.