This article analyzes a specific bipartite network that shows the relationships between users and anime, examining how the descriptions of anime influence the formation of user communities. In particular, we introduce a new variable that quantifies the frequency with which words from a description appear in specific word clusters. These clusters are generated from a bigram analysis derived from all descriptions in the database. This approach fully characterizes the dynamics of these communities and shows how textual content affect the cohesion and structure of the social network among anime enthusiasts. Our findings suggest that there may be significant implications for the design of recommendation systems and the enhancement of user experience on anime platforms.

翻译：本文分析了一个展示用户与动漫之间关系的特定二分网络，探讨了动漫描述如何影响用户社区的形成。特别地，我们引入了一个新变量，用于量化描述中的词语在特定词语簇中出现的频率。这些词语簇是通过对数据库中所有描述进行二元语法分析而生成的。该方法完整刻画了这些社区的动态特征，并展示了文本内容如何影响动漫爱好者社交网络的凝聚力和结构。我们的研究结果表明，这对于推荐系统的设计以及动漫平台用户体验的提升可能具有重要启示。