Overview of the Altmetrics Landscape

Abstract

While the impact of article citations has been examined for decades, the “altmetrics” movement has exploded in the past year. Altmetrics tracks the activity on the Social Web and looks at research outputs besides research articles. Publishers of scientific research have enabled altmetrics on their articles, open source applications are available for platforms to display altmetrics on scientific research, and subscription models have been created that provide altmetrics. In the future, altmetrics will be used to help identify the broader impact of research and to quickly identify high-impact research. Altmetrics and Article-Level Metrics The term “altmetrics” was coined by Jason Priem, a PhD candidate at the School of Information and Library Science at University of North CarolinaChapel Hill. According to the Altmetrics Manifesto, altmetrics is “the creation and study of new metrics based on the Social Web for analyzing and, information scholarship” (Altmetrics.org, http://altmetrics.org/about). Altmetrics is data points that are generated more rapidly than traditional metrics, such as citations, so researchers do not have to wait years to show their worth. Altmetrics attempts to provide timely measures of an impact through the use of metrics from HTML views and downloads of scholarly articles, blog posts, Tweets, bookmarks, etc. By providing real-time (or near real-time) information, altmetrics can be used to show the merit of scientific research not just by researchers (through citations) but also the impact of the research to the public (through social media channels). The altmetrics movement builds on previous work by other researchers. Johan Bollen has been studying usage on articles for over a decade. He started MESUR (http://mesur.informatics. indiana.edu/) in 2006 as a large-scale usage data collection for scientific research. The MESUR database currently contains over one billion article-level usage events obtained from publishers, institutions, and aggregators. Eigenfactor is a rating of the total importance of a scientific journal. It was created in 2007 by Jevin West and Carl Bergstrom of the University of Washington as an academic research project to rank journals based on a vast network of citations (Eigenfactor.org, http://www.eigenfactor.org/ whyeigenfactor.php). Article-Level Metrics (ALM) are a comprehensive and multi-dimensional suite of transparent and established metrics at the article level (http://article-level-metrics.plos.org/alm-info/). Article-Level Metrics includes many of the same data points at altmetrics, but also includes usage statistics and traditional metrics such as the number of citations to an article. Article-Level Metrics are typically associated with the publisher PLOS (Public Library of Science) who introduced the metrics on all PLOS articles in 2009.