Year: 2013
Type: article
Abstract: The number of academic articles published annually has risen exponentially in the past decade, making our jobs as librarians ever more challenging as we assist patrons in finding exactly what it is that they are looking for. \n \nAt the same time, traditional measures of research quality such as the journal impact factor and citation counts have been called into question for being unreliable and slow to accumulate. Though these measures have helped librarians filter for quality content in the past, they show weakness when applied to the rapidly evolving scholarly publication marketplace. Neither can be easily applied to non-traditional scholarly outputs such as working papers, technical reports, data sets, or conference presentations. \n \nWe have also recently seen a rise in Open Access (OA) publications, which make research easier to access than ever before. Megajournals such as PLOS ONE and Sage Open publish more articles in a day than some journals do in a year. The sheer volume of available scholarship is enough to make one’s head spin. \n \nGiven these challenges, how can librarians help patrons access what they seek while at the same time make our own jobs easier as we sift through the ever-rising sands of available scholarship? \n \nEnter altmetrics, a new approach to determining the quality and popularity of research more quickly than ever before. Altmetrics (http://altmetrics.org/manifesto/) tally online shares, saves, reviews, adaptations, and social media usage related to research outputs of all kinds—not only traditional publications but also grey literature, digital scholarship, research blogs, datasets, and other modes of scholarly communication. When paired with usage statistics (downloads and pageviews) and traditional measures of impact (journal impact factors and citation counts), they can be an excellent way to help sift through high-quality and popular search results to zero in on what patrons seek.
Author: Stacy Konkiel
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W122364674