Research on pathways of expert finding on academic social networking sites

The advent of academic social networking sites (ASNS) has provided a more convenient way for users to seek out experts. This paper uses ResearchGate to explore the features of pathways through four different tasks, combined with questionnaires and interviews. These tasks are aimed at identifying the right experts with relevant expertise or experience for a given topic. We propose a pathway-based approach that takes into consideration both pages and navigations. The pathways show the whole process of how users find experts on ASNS for a variety of reasons. A user visiting ASNS will generate different types of pages, and navigation represents the act of moving from one page to another. A series of navigations between pages that can be linked together chronologically make up the pathways. A total of 94 valid pathways were used for the cluster analysis. The results show that the pages most frequently accessed by users are profile pages, search pages, and publication pages. A comparison of these three types found that the overall utilization of publication pages is low. Users pay more attention to research results pages within profile pages, and continuously adjust the queries on demand. Single seeking pathways, triangular seeking pathways and multiple seeking pathways are identified to understand the process of users' expert finding. Finally, this paper proposes implications for the interface design of ASNS: improve search pages, focus on users' personalized needs, and apply relational networks in the seeking process. Furthermore, the findings have a positive impact on encouraging interaction, collaboration and innovation in the research environment.