A recurrent finding in personal network research is that individual and social outcomes are influenced not just by the kind of people one knows, but also by how those people are connected to each other. Personal network structure – the way in which one’s personal contacts know and interact with each other – reflects broader trends in social organization and personal communities, and shapes patterns of social capital, support, and isolation. This article proposes a method to identify typologies of structure in large collections of personal networks. The method is applied to six datasets collected in widely different circumstances and using various survey instruments. It is then compared with another recently introduced method to extract typologies of egocentric network structure. Findings show that personal network structure can be effectively summarized using just three measures of cohesive subgroup characteristics. Structural typologies can then be identified by applying standard cluster analysis techniques to the three variables. Both methods considered in the article capture significant variation in network structures, but they also show substantial levels of disagreement and cross-classification. I discuss similarities and differences between the methods, and potential applications of the proposed typologies to substantive research on personal communities, social support, and social capital.

The paper explores the relationship between personality characteristics, sense of community and the structure of personal networks. We collected personal network data from 100 adults, consisting of the information about their 45 alters and ties among them. In addition to the typically used bivariate correlations to analyze the relationship between individual psychological differences and network structure, we propose first the use of typologies of networks and personality and second modified versions of the triadic census in ego-networks. The results show that different personality types tend to occupy a different kind of networks and that newly introduced triadic measures show a relatively higher association with examined psychological attributes than global network measures. Overall, the Psychological Sense of Community showed higher associations with network measures than Big Five personality traits. The former was positively correlated with measures of closed triads among alters, but also with alters embedded in triads with weak ties. Regarding personality traits, Emotional Stability was positively correlated with strong closed triads and with the overall indicator of density. The elaboration of typologies and the census of triads are shown to be effective strategies for the description of personal networks, as well as for the analysis of individual psychological differences.

Name generators (NGs) and position generators (PGs) have been used to measure resources embedded in personal relationships, namely social support and social capital, respectively. Comparisons of these measures adopted NGs that only elicit a small number of alters (max. 5). In this paper we explore whether the measurement of social capital with NGs eliciting larger personal networks (say 15 to 20 alters) gives more comparable results to the PG in terms of occupational prestige. To address this issue, we designed a personal network questionnaire that combined a multiple name generator (MNG) and a PG and enquired about alter characteristics and alter-alter ties for the two sets of nominations simultaneously, allowing their integrated analysis. The questionnaire was implemented in the software EgoNet to collect data from social/environmental entrepreneurs in Spain (N = 30) and Mexico (N = 30. The analysis shows that the two approaches capture mostly non-overlapping sets of personal network members, suggesting that the PG measured in this case available, but not accessed social capital. Remarkably the NG led to a higher average prestige for this occupational group than the PG, but also a lower heterogeneity in prestige. The consequences of using one or another approach and their interpretations are discussed.

This paper examines the stability of egocentric networks as reported over time using a novel touchscreen-based participant-aided sociogram. Past work has noted the instability of nominated network alters, with a large proportion leaving and reappearing between interview observations. To explain this instability of networks over time, researchers often look to structural embeddedness, namely the notion that alters are connected to other alters within egocentric networks. Recent research has also asked whether the interview situation itself may play a role in conditioning respondents to what might be the appropriate size and shape of a social network, and thereby which alters ought to be nominated or not. We report on change in these networks across three waves and assess whether this change appears to be the result of natural churn in the network or whether changes might be the result of factors in the interview itself, particularly anchoring and motivated underreporting. Our results indicate little change in average network size across waves, particularly for indirect tie nominations. Slight, significant changes were noted between waves one and two particularly among those with the largest networks. Almost no significant differences were observed between waves two and three, either in terms of network size, composition, or density. Data come from three waves of a Chicago-based panel study of young men who have sex with men.

When collecting egocentric network data, visual representations of networks can function as a cognitive aid for depicting relationships, helping to maintain an overview of the relationships, and keeping the attention of the interviewees. Additionally, network maps can serve as a narration generator in qualitative and in mixed-methods studies. While varying visual instruments are used for collecting egocentric network data, little is known about differences among visual tools concerning the influence on the resulting network data, the usability for interviewees, and data validity. The article provides an overview of existing visually oriented tools that are used to collect egocentric networks and discusses their functions, advantages, and limitations. Then, we present results of an experimental study where we compare four different visual tools with regard to networks elicited, manageability, and the impact of follow-up questions. In order to assess the manageability of the four tools, we used the thinking aloud method. The results provide evidence that the decision in favor of a specific visual tool (structured vs. unstructured) can affect the size and composition of the elicited networks. Follow-up questions greatly affect the elicited networks and follow-up cues can level out differences among tools. Respondents tend to prefer the concentric circles tool, with some differences in preferences and manageability of tools between participants with low and those with high socioeconomic status. Finally, assets and drawbacks of the four instruments are discussed with regard to data quality and crucial aspects of the data collection process when using visual tools.

We report on an interview method using photo-based network elicitation and a landmark anchoring event to collect data on relationship change in ego networks retrospectively. Using the wedding albums of married or formerly married respondents, we populate a network from many years ago with persons pictured in the album and then collect data about each respondent’s relationship with each person at the time of the wedding and at the time of the interview. This data collection method mitigates many of the problems associated with retrospective data collection and does not have the logistical difficulties associated with panel studies. Our findings show that this method is successful in collecting significant numbers of connections that have undergone change, and especially reductions in activity along various dimensions.

It is well documented that intergenerational ties play important roles in adults’ well-being. However, most studies focus on the impact of individuals’ own perceptions of their ties without considering whether family members’ assessments of these ties affect well-being. We address this question using data from 296 adult children nested within 95 later-life families in which all offspring were interviewed. Applying a mixed-method within-family approach, we explored whether the effect of perceived maternal favoritism on depressive symptoms was increased when siblings shared ego’s perceptions. Multilevel regression analyses revealed that ego’s own perceptions predicted depressive symptoms, but only among daughters. Siblings’ perceptions that egos were most close to mothers did not affect the well-being of daughters or sons. Qualitative analyses suggested that differential effects of perceived favoritism by gender reflected differences in the meaning sons and daughters associated with being favored children. Favored daughters were more likely than favored sons to report that they were emotional caregivers to their mothers; this pattern was especially strong when siblings reinforced egos’ perceptions of being “best suited” for this role. These findings emphasize the salience of egos’ own perceptions, relative to those of family network members, in shaping role embracement and psychological well-being, especially among women.