Wu, D., Fan, S., & Yuan, F. (2021). Research on pathways of expert finding on academic social networking sites. Information Processing & Management, https://doi.org/10.1016/j.ipm.2020.102475.

Abstract

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.

摘要

学术社交网站（ASNS）的出现为用户提供了一种更方便的专家方式。本文使用ResearchGate通过四个不同的任务，结合问卷和访谈来探索路径的特征。这些任务旨在确定具有特定主题的相关专业知识或经验的合适专家。我们提出了一种基于路径的方法，该方法同时考虑了页面和导航。这些途径显示了用户出于各种原因在 ASNS 上查找专家的整个过程。访问 ASNS 的用户将生成不同类型的页面，导航表示从一个页面移动到另一个页面的操作。页面之间的一系列导航可以按时间顺序链接在一起，构成了路径。共使用94个有效途径进行聚类分析。结果显示，用户最常访问的页面是个人资料页面、搜索页面和出版物页面。对这三种类型的比较发现，出版物页面的总体利用率较低。用户更加关注个人资料页面中的研究结果页面，并根据需要不断调整查询。识别单一寻路、三角寻路和多寻路，了解用户专家找路的过程。最后，本文对ASNS的界面设计提出了启示：改进搜索页面，关注用户的个性化需求，并在搜索过程中应用关系网络。此外，这些发现对鼓励研究环境中的互动，协作和创新产生了积极影响。