Source: Think Links
One of the ideas in the altmetrics manifesto was that almetrics allow a diversity of metrics. With colleagues in the VU University Amsterdam’s Network Institute, we’ve been investigating the use of online data (in this case google scholar) to help create new metrics to measure the independence of researchers. In this case, we need fresh data to establish whether an emerging scholar is becoming independent from their supervisor. We just had the results of one our approaches accepted into the Web Science 2013 conference. The abstract is below and here’s a link to the preprint.
Identifying Research Talent Using Web-Centric Databases
Anca Dumitrache, Paul Groth, and Peter van den Besselaar
Metrics play a key part in the assessment of scholars. These metrics are primarily computed using data collected in offline procedures. In this work, we compare the usage of a publication database based on a Web crawl and a traditional publication database for computing scholarly metrics. We focus on metrics that determine the independence of researchers from their supervisor, which are used to assess the growth of young researchers. We describe two types of graphs that can be constructed from online data: the co-author network of the young researcher, and the combined topic network of the young researcher and their supervisor, together with a series of network properties that describe these graphs. Finally, we show that, for the purpose of discovering emerging talent, dynamic online resources for publications provide better coverage than more traditional datasets.
This is fairly preliminary work, it mainly establishes that we want to use the freshest possible data for this work. We are expanding the work to do a large scale study of independence as well as to use different sources of data. But to me, this shows how the freshness of web data allows us to begin looking at and measuring research in new ways.
Filed under: altmetrics Tagged: #altmetrics, independence indicator, web science, websci13 
