Network representation is a crucial topic in historical social network analysis. The debate around their value and connotations, led by humanist scholars, is today more relevant than ever, seeing how common these representations are as support for historical analysis. Force-directed networks, in particular, are popular as they can be developed relatively quickly, and reveal patterns and structures in data. The underlying algorithms, although powerful in revealing hidden patterns, do not retain meaningful structure and existing hierarchies within historical social networks. In this article, we question the foreign aspect of this structure that force-directed layout create in historical datasets. We explore the importance of hierarchy in social networks, and investigate whether hierarchies -- strongly present within our models of social structure -- affect our perception of social network data. Results from our user evaluation indicate that hierarchical network representations reduce cognitive load and leads to more frequent and deeper insights into historical social networks. We also find that users report a preference for the hierarchical graph representation. We analyse these findings in light of the broader discussion on the value of force-directed network representations within humanistic research, and introduce open questions for future work in this line of research.
翻译:在历史社会网络分析中,网络代表性是一个至关重要的专题。由人道主义学者领导的关于其价值和内涵的辩论在今天比以往任何时候更加相关,我们看到这些代表性对于历史分析的支持是何等常见的。尤其是,部队领导的网络由于能够相对快速地发展而广受欢迎,能够揭示数据的模式和结构。基本算法虽然在揭示隐藏模式方面力量强大,但并不保留历史社会网络中有意义的结构和现有等级结构。在本条中,我们质疑这种结构的外部方面,这种结构是由武力主导的布局在历史数据集中产生的。我们探讨社会网络等级的重要性,并调查在社会结构模型中强烈存在的等级划分是否影响我们对社会网络数据的看法。我们的用户评价结果表明,等级网络的表示减少了认知负荷,并导致对历史社会网络的更频繁和更深入的洞察。我们还发现,用户报告倾向于使用等级图表示。我们根据对人文研究中武力导向网络表示的价值的更广泛讨论来分析这些结论。我们为今后研究方针的工作提出开放的问题。