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子群体在获取和/或使用数字技术方面存在的差距。例如，与年轻人相比，老年人拥有宽带连接、使用互联网和采用新技术的倾向较低。基于对数字技术使用异质性的分析，我们构建了一个关于三个欧洲国家（芬兰、意大利和保加利亚）个体拥有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（正式称为发送节点和接收节点）之间的关系提供了有效的结构。目标是针对每个国家，根据个体的数字技能（接收节点）对其进行聚类（发送节点）。为此，我们采用考虑伴随变量的潜在特质分析混合模型（Mixture of Latent Trait Analyzers, MLTA），该模型允许我们：(i) 根据个体特征对个体进行聚类；(ii) 分析社会经济和人口统计学特征及代际联系如何影响个体数字化程度。结果显示，数字化类型主要取决于年龄、收入和教育水平，而家庭中是否有儿童仅在意大利和芬兰的数字化进程中发挥重要作用。