面向出版网络探索的局部内聚最大化算法

27th International Conference on Science, Technology and Innovation Indicators (STI 2023) Pub Date : 2023-05-14 DOI:10.55835/644122df83bc0caad0e3333d

Matthias Held, Bastian Steudel, J. Gläser

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引用次数: 0

摘要

科学主题重建的主要方法是应用全局社区检测算法。然而，这些算法的一些特性与社会学对主题的讨论发生了冲突。我们在此提出了一种新的局部文献计量算法，该算法符合主题的社会学定义，并在局部重建文献计量网络中的密集区域。

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A local cohesion-maximising algorithm for the exploration of publication networks

The dominant approach to the reconstruction of scientific topics is the application of global community detection algorithms. Some of the properties of these algorithms, however, collide with the sociological discussion on topics. We present here for consideration a new local bibliometric algorithm that is in line with sociological definitions of topics and which reconstructs dense regions in bibliometric networks locally.

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来源期刊

27th International Conference on Science, Technology and Innovation Indicators (STI 2023)

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