论文标题
基于15世纪意大利战争的社区检测和社交网络分析
Community detection and Social Network analysis based on the Italian wars of the 15th century
论文作者
论文摘要
在这项贡献中，我们通过将人类互动作为基础来研究社交网络建模。为此，我们提出了一组新的功能，即亲和力，旨在捕获网络中每对参与者之间局部互动的性质。通过使用这些功能，我们开发了一种新的社区检测算法，即Borgia聚类，社区自然源于网络中的多代理交互。我们还讨论了大小和规模对社区的影响，以及在大社区出现时如何应对额外的复杂性。最后，我们将我们的社区检测解决方案与其他代表性算法进行比较，从而找到有利的结果。
In this contribution we study social network modelling by using human interaction as a basis. To do so, we propose a new set of functions, affinities, designed to capture the nature of the local interactions among each pair of actors in a network. By using these functions, we develop a new community detection algorithm, the Borgia Clustering, where communities naturally arise from the multi-agent interaction in the network. We also discuss the effects of size and scale for communities regarding this case, as well as how we cope with the additional complexity present when big communities arise. Finally, we compare our community detection solution with other representative algorithms, finding favourable results.
