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Review
. 2015 Jun 5;25(2):152-60.
doi: 10.11613/BM.2015.016. eCollection 2015.

Altmetrics - a complement to conventional metrics

Remedios Melero  1
Affiliations
Review

Altmetrics - a complement to conventional metrics

Remedios Melero. Biochem Med (Zagreb). .

Abstract

Emerging metrics based on article-level does not exclude traditional metrics based on citations to the journal, but complements them. Both can be employed in conjunction to offer a richer picture of an article use from immediate to long terms. Article-level metrics (ALM) is the result of the aggregation of different data sources and the collection of content from multiple social network services. Sources used for the aggregation can be broken down into five categories: usage, captures, mentions, social media and citations. Data sources depend on the tool, but they include classic metrics indicators based on citations, academic social networks (Mendeley, CiteULike, Delicious) and social media (Facebook, Twitter, blogs, or Youtube, among others). Altmetrics is not synonymous with alternative metrics. Altmetrics are normally early available and allow to assess the social impact of scholarly outputs, almost at the real time. This paper overviews briefly the meaning of altmetrics and describes some of the existing tools used to apply this new metrics: Public Library of Science--Article-Level Metrics, Altmetric, Impactstory and Plum.

Keywords: altmetrics; article-level metrics; citation; social media.

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Conflict of interest statement

None declared.

Figures

Figure 1
Figure 1
How is the measure of impact in terms of traditional metrics and altmetrics (9). Measurements at personal and article-levels increase granularity (disaggregation from journals as entities). Altmetrics provide impact at real time (immediate), while traditional methods need longer times to facilitate impact data.
Figure 2
Figure 2
Screenshot showing two examples of two papers that received a high attention online according Altmetric data.
Figure 3
Figure 3
Screenshot of an item deposit in the institutional repository of Queensland University of Technology, showing a summary of the article statistics, including altmetrics (left bottom corner of the screenshot).
Figure 4
Figure 4
Fictional example of an Impactstory profile. Users create their CVs by uploading their works (articles, slides presentations, code, datasets, posters and web pages) and Impactstory provides various statistics including information about how to reference any item, its DOI, PubMed ID, and allows CVs to be downloaded in comma separated value (.csv) format.
Figure 5
Figure 5
Effect of social networks (Twitter) on the impact and downloads of an open access paper deposited in a repository (22).
See this image and copyright information in PMC

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