An initial log analysis of usage patterns on a research networking system.

Usage data for research networking systems (RNSs) are valuable but generally unavailable for understanding scientific professionals' information needs and online collaborator seeking behaviors. This study contributes a method for evaluating RNSs and initial usage knowledge of one RNS obtained from using this method. We designed a log for an institutional RNS, defined categories of users and tasks, and analyzed correlations between usage patterns and user and query types. Our results show that scientific professionals spend more time performing deep Web searching on RNSs than generic Google users and we also show that retrieving scientist profiles is faster on an RNS than on Google (3.5 seconds vs. 34.2 seconds) whereas organization-specific browsing on a RNS takes longer than on Google (117.0 seconds vs. 34.2 seconds). Usage patterns vary by user role, e.g., faculty performed more informational queries than administrators, which implies role-specific user support is needed for RNSs.