ABSTRACT

Community detection is a major issue in network analysis. This paper combines a socio-historical approach with an experimental reconstruction of programs to investigate the early automation of clique detection algorithms, which remains one of the unsolved NP-complete problems today. The research led by the archaeologist Jean-Claude Gardin from the 1950s on non-numerical information and graph analysis is retraced to demonstrate the early contributions of social sciences and humanities. The limited recognition and reception of Gardin's innovative computer application to the humanities are addressed through two factors, in addition to the effects of historiography and bibliographies on the recording, discoverability, and reuse of scientific productions: (1) funding policies, evidenced by the transfer of research effort on graph applications from temporary interdisciplinary spaces to disciplinary organizations related to the then-emerging field of computer science; and (2) the erratic careers of algorithms, in which efficiency, flaws, corrections, and authors' status, were determining factors.

摘要

社区检测是网络分析中的一个主要问题。本文将社会历史方法与程序的实验重建相结合，以研究团检测算法的早期自动化，这仍然是当今未解决的 NP 完全问题之一。1950 年代考古学家 Jean-Claude Gardin 领导的关于非数字信息和图形分析的研究被追溯以证明社会科学和人文科学的早期贡献。除了史学和书目对科学成果的记录、可发现性和再利用的影响之外，Gardin 对人文科学的创新计算机应用的有限认可和接受还通过两个因素得到解决：(1) 资助政策，图应用研究工作从临时跨学科空间转移到与当时新兴的计算机科学领域相关的学科组织就证明了这一点；(2) 算法的职业生涯不稳定，其中效率、缺陷、更正和作者的地位是决定因素。