Social support is a crucial factor for first-generation students’ (FGS) integration at university and their educational success. FGS are often assumed to lack social support and integration, but research shows mixed results. By means of a mixed-methods approach (combination of interviews and online survey), we aimed to shed light on the characteristics in FGS social networks that classify them as high-quality networks in order to obtain a deeper understanding of the structure and setup of the social contexts from which FGS receive support. Using these characteristics, we constructed types of socially supported students and related them to academic success. For that, we conducted N = 40 semi-structured interviews linked to Qualitative Social Network Analysis at an urban German University. Prior to the interviews, the interviewees filled out an online survey (1) consisting of demographic variables and psychological scales. During the interviews (2), we followed a problem-centred interview approach for the first part and then (3) asked about the FGS’s support networks during the beginning of their bachelor’s degrees. All the interviews were coded by applying content analysis. Network maps were analysed using qualitative structural analysis (QSA). Both maps and codes were used to build three types of support as received by the students. These types were in turn connected to the results of the support forms in content analysis and the psychometric scales to estimate how students perceive different structures in their networks as supportive. The results revealed three types: small and dense bijou networks, medium networks with emotionally close alters (close-knit networks), and large and diverse networks (have-it-all networks). The types show different results for university success and perceived support for their networks.

社会支持是大学第一代学生（FGS）融入和他们的教育成功的关键因素。人们通常认为FGS缺乏社会支持和融合，但研究表明结果参差不齐。通过混合方法（访谈和在线调查相结合），我们旨在阐明FGS社交网络中将其归类为高质量网络的特征，以便对这些结构和设置有更深入的了解。 FGS从中获得支持的社会环境。利用这些特征，我们构建了受社会支持的学生类型，并将其与学业成就联系在一起。为此，我们进行了N =与城市德国大学的定性社会网络分析相关的40个半结构化访谈。在访谈之前，受访者填写了一项在线调查（1），其中包括人口统计变量和心理量表。在面试期间（2），我们首先采用以问题为中心的面试方法，然后（3）询问FGS在其学士学位开始时的支持网络。所有访谈均采用内容分析进行编码。使用定性结构分析（QSA）分析网络图。地图和代码都被用来构建学生所接受的三种类型的支持。这些类型又与内容分析和心理测验量表中的支持表格的结果相关，以估计学生如何将其网络中的不同结构视为支持对象。结果揭示了三种类型：小型和密集的bijou网络，具有情感上紧密变化的中等网络（紧密联系的网络）以及大型多样的网络（拥有所有网络）。这些类型显示出不同的结果，表明大学获得了成功，并获得了对其网络的支持。