The digital divide is the gap among population sub-groups in accessing and/or using digital technologies. For instance, older people show a lower propensity to have a broadband connection, use the Internet, and adopt new technologies than the younger ones. Motivated by the analysis of the heterogeneity in the use of digital technologies, we build a bipartite network concerning the presence of various digital skills in individuals from three different European countries: Finland, Italy, and Bulgaria. Bipartite networks provide a useful structure for representing relationships between two disjoint sets of nodes, formally called sending and receiving nodes. The goal is to perform a clustering of individuals (sending nodes) based on their digital skills (receiving nodes) for each country. In this regard, we employ a Mixture of Latent Trait Analyzers (MLTA) accounting for concomitant variables, which allows us to (i) cluster individuals according to their individual profile; (ii) analyze how socio-economic and demographic characteristics, as well as intergenerational ties, influence individual digitalization. Results show that the type of digitalization substantially depends on age, income and level of education, while the presence of children in the household seems to play an important role in the digitalization process in Italy and Finland only.

翻译：数字鸿沟是指不同人口亚群体在接入和/或使用数字技术方面存在的差距。例如，老年人相比年轻人，在拥有宽带连接、使用互联网以及采用新技术方面表现出较低的倾向。受分析数字技术使用异质性动机的驱动，我们构建了一个关于来自三个欧洲国家（芬兰、意大利和保加利亚）个体所具备多种数字技能的二分网络。二分网络为表示两个不相交节点集（形式上称为发送节点和接收节点）之间的关系提供了有用的结构。目标是基于每个国家个体的数字技能（接收节点）对其进行聚类（发送节点）。为此，我们采用了考虑伴随变量的潜在特质分析混合模型（MLTA），该模型使我们能够：（i）根据个体概况对个体进行聚类；（ii）分析社会经济和人口特征以及代际联系如何影响个体数字化水平。结果表明，数字化类型在很大程度上取决于年龄、收入和教育水平，而家庭中是否有子女似乎仅在意大利和芬兰的数字化进程中发挥重要作用。