ENTRIES TAGGED "altmetrics"
The digital transformation in publishing is bringing forth more than new reading platforms, gadgets and distribution options — it also brings a wealth of data publishers have never before had access to, data that can be applied to new marketing and production strategies, and used to help create more efficient business models.
As data becomes more and more central to publishing ecosystems, traditional methods of metric collection and analysis are proving insufficient. This need for new measurement techniques has given rise to a new metrics approach called “alternative metrics.” I reached out to Todd Carpenter, Executive Director of NISO, to find out what’s behind the changing data needs and more about how altmetric applications can benefit publishers. Carpenter will explore this topic further at TOC Frankfurt on October 9, 2012. Our interview follows.
What are alternative metrics?
Todd Carpenter: Alternative metrics — referred to as “altmetrics” — are a suite of assessment criteria and measures that are being developed, particularly in the scientific and academic communities, to assess the importance of a particular work of scholarly output in a new way.
Traditional metrics have been downloads, citations, or sales — generally based on publication-level data. For example, the Thomson Reuters Impact Factor, one of the most widely used metrics in scholarly publishing, measures quality at the journal level by measuring the number of citations to it in other journal articles. As academic publishing has expanded and diversified, these traditional metrics have been increasingly criticized for issues such as their granularity (i.e., measuring at the publication level, not the item level), or their bias toward citation, which is a common practice among researchers but doesn’t reflect more applied, practical, or public use.
The scope of measures that could be considered altmetrics is actually quite broad, ranging from analysis of usage data to social media references; Google Page Rank; deep statistical data analysis techniques, such as betweenness centrality; and other relatedness statistical measures. Also considered for inclusion in alternative metrics are measures of non-traditional types of content production, such as the release of scientific data sets, blog posting, or social media activity — none of which are addressed in traditional metrics.