scholarly journals Structure in personal networks: Constructing and comparing typologies

2019 ◽  
Vol 8 (2) ◽  
pp. 142-167
Author(s):  
Raffaele Vacca
Keyword(s):  
Social Capital ◽  
Network Structure ◽  
Personal Networks ◽  
Personal Network ◽  
Cohesive Subgroup ◽  
Potential Applications ◽  
Egocentric Network ◽  
Survey Instruments ◽  
Cross Classification ◽  
Personal Communities

AbstractA 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.

Patterns of support and conflict relationships in personal networks and perceived stress

2020 ◽  
pp. 001139212094892
Author(s):  
Gaëlle Aeby ◽  
Jacques-Antoine Gauthier ◽  
Eric D Widmer
Keyword(s):  
Social Capital ◽  
Perceived Stress ◽  
Emotional Support ◽  
Personal Networks ◽  
Life Domains ◽  
Mutual Support ◽  
Personal Network ◽  
Bonding Social Capital ◽  
Relational Patterns ◽  
Bridging Social Capital

This article investigates the association between personal networks and stress, both positively through support and negatively through conflict. In a representative sample of 755 individuals residing in Switzerland, each individual was asked to name people in their lives who they perceived as very important, as well as to report their mutual support and conflict interactions. First, the article develops and investigates a typology with five relational patterns based on indicators of emotional support and conflict relationships in personal networks. These patterns are the following: bonding social capital, bridging social capital, ego-centered conflict, overload, and ambivalent. Second, it explores the association of these patterns with stress levels that are perceived in various life domains. Results show that individuals involved in relationships that were predominantly supportive had lower levels of stress, whereas individuals experiencing relationships characterized by conflict, or an imbalance in support by giving more than receiving, had higher levels of stress. Finally, ambivalent relationships in which support and conflict were equally present were associated with an intermediate level of stress. These results show the importance of considering support and conflict relationships together in personal network structures.

The embeddedness of social capital in personal networks

2019 ◽  
Vol 8 (2) ◽  
pp. 189-203
Author(s):  
José Luis Molina ◽  
Alejandro García-Macías ◽  
Miranda J. Lubbers ◽  
Hugo Valenzuela-Garcia
Keyword(s):  
Social Support ◽  
Social Capital ◽  
Occupational Group ◽  
Personal Relationships ◽  
Personal Networks ◽  
Integrated Analysis ◽  
Occupational Prestige ◽  
Personal Network ◽  
Social Environmental ◽  
Overlapping Sets

AbstractName 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.

Important relationships in a multilevel world: The role of network structure in explaining closeness of relationships and access to resources in later life

2021 ◽  
pp. 026540752110093
Author(s):  
Mahin Raissi ◽  
Robert Ackland
Keyword(s):  
Social Networks ◽  
Statistical Model ◽  
Network Structure ◽  
Online Social Networks ◽  
Later Life ◽  
Personal Networks ◽  
Network Data ◽  
Personal Network ◽  
Access To Resources

We examine why some relationships are more important than others, using a multilevel statistical model and data on personal networks of Australians 50 years and older, collected via a purpose-built Facebook application. While the network data were collected automatically, participants in our study provided data on the importance of their relationships, measured by perceived closeness and access to resources. We find that the information on how network members are connected with each other (network structure) provides powerful insights into what makes a relationship important. When importance is measured by closeness of relationship, important alters are kin, and are alters who are highly connected with others or act as bridges between different groups. When importance is measured by access to resources, important alters are those who act as bridges and are in more densely-knit networks. We discuss our findings in a broader context of research into important relationships in later life, and collecting personal network data via online social networks.

scholarly journals An Egocentric Network Contact Tracing Experiment: Testing Different Procedures to Elicit Contacts and Places

2021 ◽  
Vol 18 (4) ◽  
pp. 1466
Author(s):  
Andrew Pilny ◽  
C. Joseph Huber
Keyword(s):  
Social Network ◽  
Infectious Diseases ◽  
Effect Size ◽  
Survey Methods ◽  
Contact Tracing ◽  
Medium Effect ◽  
Physiological Variables ◽  
Medium Effect Size ◽  
Egocentric Network ◽  
Survey Instruments

Contact tracing is one of the oldest social network health interventions used to reduce the diffusion of various infectious diseases. However, some infectious diseases like COVID-19 amass at such a great scope that traditional methods of conducting contact tracing (e.g., face-to-face interviews) remain difficult to implement, pointing to the need to develop reliable and valid survey approaches. The purpose of this research is to test the effectiveness of three different egocentric survey methods for extracting contact tracing data: (1) a baseline approach, (2) a retrieval cue approach, and (3) a context-based approach. A sample of 397 college students were randomized into one condition each. They were prompted to anonymously provide contacts and populated places visited from the past four days depending on what condition they were given. After controlling for various demographic, social identity, psychological, and physiological variables, participants in the context-based condition were significantly more likely to recall more contacts (medium effect size) and places (large effect size) than the other two conditions. Theoretically, the research supports suggestions by field theory that assume network recall can be significantly improved by activating relevant activity foci. Practically, the research contributes to the development of innovative social network data collection methods for contract tracing survey instruments.

scholarly journals Measuring Social Capital and Support Networks of Young Immigrants

2016 ◽  
Vol 9 (5) ◽  
pp. 62
Author(s):  
María Paz Sandín Esteban ◽  
Angelina Sánchez Martí ◽  
Ana Belén Cano Hila
Keyword(s):  
Social Capital ◽  
Educational Outcomes ◽  
Compulsory Education ◽  
Academic Persistence ◽  
Methodological Framework ◽  
Personal Network ◽  
The Social ◽  
Relational Systems ◽  
The Impact ◽  
Young Immigrants

<p class="apa">This paper addresses the importance of the diagnosis of “personal communities” as relational systems that may influence the academic pathways of young immigrants. As part of a longitudinal study of the academic persistence of young people in their transition from compulsory to post-compulsory education, a “personal network questionnaire” has been developed. This instrument allows the relational structure of students to be captured and represented, and the impact of this structure on educational outcomes to be analysed. It measures and explores the network of inter-relations with adults (family, educational and recreational professionals, etc.) and peers in different settings. The theoretical elements underpinning its design and implementation are the interweaving of the student social capital and social support system to which they have or may have access to, and the Social Network Analysis (SNA) approach as the methodological framework. This network approach is rendered highly significant and valuable for professionals in educational diagnosis to assess relational vulnerability and design programs of intervention and counseling. With graphic techniques, we can somewhat address this challenge by examining patterns in relational data, experimenting with these data and putting forward hypotheses.</p>

Personal networks and psychological attributes: Exploring individual differences in personality and sense of community and their relationship to the structure of personal networks

2019 ◽  
Vol 8 (2) ◽  
pp. 168-188 ◽  
Author(s):  
Isidro Maya-Jariego ◽  
Srebrenka Letina ◽  
Elena González Tinoco
Keyword(s):  
Personality Traits ◽  
Sense Of Community ◽  
Personal Networks ◽  
Global Network ◽  
Personal Network ◽  
Ego Networks ◽  
Network Measures ◽  
Psychological Attributes ◽  
Psychological Differences ◽  
The Relationship

AbstractThe 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.

scholarly journals Head-to-Head Comparison of Social Network Assessments in Stroke Survivors

2020 ◽  
Vol 11 (1) ◽  
pp. 18-24
Author(s):  
Morgan Prust ◽  
Abby Halm ◽  
Simona Nedelcu ◽  
Amber Nieves ◽  
Amar Dhand
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Social Network ◽  
Social Isolation ◽  
Network Structure ◽  
Network Size ◽  
Personal Network ◽  
Mapping Tool ◽  
Social Network Structure ◽  
Network Mapping

Background and Purpose: Social networks influence human health and disease through direct biological and indirect psychosocial mechanisms. They have particular importance in neurologic disease because of support, information, and healthy behavior adoption that circulate in networks. Investigations into social networks as determinants of disease risk and health outcomes have historically relied on summary indices of social support, such as the Lubben Social Network Scale–Revised (LSNS-R) or the Stroke Social Network Scale (SSNS). We compared these 2 survey tools to personal network (PERSNET) mapping tool, a novel social network survey that facilitates detailed mapping of social network structure, extraction of quantitative network structural parameters, and characterization of the demographic and health parameters of each network member. Methods: In a cohort of inpatient and outpatient stroke survivors, we administered LSNS-R, SSNS, and PERSNET in a randomized order to each patient. We used logistic regression to generate correlation matrices between LSNS-R scores, SSNS scores, and PERSNET’s network structure (eg, size and density) and composition metrics (eg, percent kin in network). We also examined the relationship between LSNS-R-derived risk of social isolation with PERSNET-derived network size. Results: We analyzed survey responses for 67 participants and found a significant correlation between LSNS-R, SSNS, and PERSNET-derived indices of network structure. We found no correlation between LSNS-R, SSNS, and PERSNET-derived metrics of network composition. Personal network mapping tool structural and compositional variables were also internally correlated. Social isolation defined by LSNS-R corresponded to a network size of <5. Conclusions: Personal network mapping tool is a valid index of social network structure, with a significant correlation to validated indices of perceived social support. Personal network mapping tool also captures a novel range of health behavioral data that have not been well characterized by previous network surveys. Therefore, PERSNET offers a comprehensive social network assessment with visualization capabilities that quantifies the social environment in a valid and unique manner.

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