Clickstream Data Yields High-Resolution Maps of Science
Johan Bollen1*, Herbert Van de Sompel1, Aric Hagberg2#, Luis Bettencourt2,3#, Ryan Chute1#, Marko A. Rodriguez2, Lyudmila Balakireva1
1 Digital Library Research and Prototyping Team, Research Library, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America, 2 Theoretical Division, Mathematical Modeling and Analysis Group, and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America, 3 Santa Fe Institute, Santa Fe, New Mexico, United States of America
Intricate maps of science have been created from citation data to visualize the structure of scientific activity. However, most scientific publications are now accessed online. Scholarly web portals record detailed log data at a scale that exceeds the number of all existing citations combined. Such log data is recorded immediately upon publication and keeps track of the sequences of user requests (clickstreams) that are issued by a variety of users across many different domains. Given these advantages of log datasets over citation data, we investigate whether they can produce high-resolution, more current maps of science.