An Initial Log Analysis of Usage Patterns on a Research Networking System

Abstract

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 types 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 vs. 34.2 seconds) while organization-specific browsing on a RNS takes longer than on Google (117.0 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.

Finding Collaborators: Toward Interactive Discovery Tools for Research Network Systems

“…Bhavnani et al [ 24 ] conducted a qualitative study of researcher needs for tools for both collaboration identification and resource discovery, identifying the need for federated information, facilities for managing large volumes of information, and “humanized computing” tools that would favor user-controlled tools over algorithmic approaches that might use opaque processes to identify suggested resources. These suggestions are consistent with the observation from Boland et al [ 12 ] that different classes of RNS users may have different goals and workflows.…”

“…To do this, they will need to provide easy access to high-quality data; in effect, they must provide added value unavailable through other means [ 6 ]. Furthermore, they must support the potentially different goals of different groups of users [ 12 ].…”

“…Research networking systems (RNSs) that model researcher activity, expertise, and collaborations have been developed to facilitate collaborator searches [ 6 - 9 ], particularly via federated search tools that provide preliminary demonstrations of cross-institution search facilities [ 10 ]. Emerging reports of RNS usage provide preliminary evidence of search and navigation patterns extracted from usage logs with deployed RNSs [ 11 , 12 ], but relatively little insight into how search tools should be designed to support the process of collaborator searches. The goal of this study was to conduct an iterative design and qualitative inquiry process to better understand scientists’ needs and workflows, and how they might best be supported by software tools.…”

“…Preliminary reports from institutional RNSs provide some insight into usage patterns and user goals. An analysis of 5 months of log data from an RNS at Columbia University found differences in usage patterns across user classes, with faculty performing more keyword searches than administrators [ 12 ]. A similar log-based analysis at the University of California, San Francisco, found that search engines were the source of almost 75% of initial visits, the number of return visitors increased over time, and that return visitors accessed a higher number of pages/visit compared to first-time users [ 11 ].…”

The Use and Significance of a Research Networking System

“…This is in contrast to findings from studies of users of Facebook where evidence suggests that users primarily reinforce existing networks, though this has only been studied in student populations [ 15 , 16 ]. In the academic setting, only one study reports use of a small private RNS showing that visitors who do log on spend more time in their session than comparable benchmarks for time spent on Google sessions [ 17 ]. In addition, several studies have documented needs and requirements for such systems to enable collaboration in science [ 18 - 20 ].…”