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Integration by Parts: Collaboration and Topic Structure in the CogSci Community
Topics in Cognitive Science ( IF 2.9 ) Pub Date : 2021-03-20 , DOI: 10.1111/tops.12526
Isabella DeStefano 1 , Lauren A Oey 1 , Erik Brockbank 1 , Edward Vul 1
Affiliation  

Is cognitive science interdisciplinary or multidisciplinary? We contribute to this debate by examining the authorship structure and topic similarity of contributions to the Cognitive Science Society from 2000 to 2019. Our analysis focuses on graph theoretic features of the co‐authorship network—edge density, transitivity, and maximum subgraph size—as well as clustering within the space of scientific topics. We also combine structural and semantic information with an analysis of how authors choose their collaborators based on their interests and prior collaborations. We compare findings from CogSci to abstracts from the Vision Science Society over the same time frame and validate our approach by predicting new collaborations in the 2020 CogSci proceedings. Our results suggest that collaboration across authors and topics within cognitive science has become increasingly integrated in the last 19 years. More broadly, we argue that a formal quantitative approach which combines structural co‐authorship information and semantic topic analysis provides inroads to questions about the level of interdisciplinary collaboration in a scientific community.

中文翻译:

按部分集成:CogSci 社区中的协作和主题结构

认知科学是跨学科的还是多学科的?我们通过检查 2000 年到 2019 年对认知科学学会的贡献的作者结构和主题相似性来为这场辩论做出贡献。我们的分析侧重于共同作者网络的图论特征——边密度、传递性和最大子图大小——作为以及科学主题空间内的聚类。我们还将结构和语义信息与作者如何根据他们的兴趣和先前的合作选择合作者的分析相结合。我们将 CogSci 的发现与同一时间范围内视觉科学协会的摘要进行比较,并通过预测 2020 CogSci 会议中的新合作来验证我们的方法。我们的研究结果表明,在过去的 19 年中,认知科学领域的作者和主题之间的合作变得越来越整合。更广泛地说,我们认为,结合结构合着信息和语义主题分析的正式定量方法为有关科学界跨学科合作水平的问题提供了途径。
更新日期:2021-04-29
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