<abstract xmlns="http://www.w3.org/1999/xhtml">

Satisfaction with any aspect of life is not easy to defined, and sometimes, it is still a topic of discussion. That is especially relevant for more excluded populations like older people. This research looked into how relevant the social support networks (SSNs) of older people are for their satisfaction with retirement, specifically in the Chilean context. It will identify some sufficient and necessary conditions for older people to be satisfied with retirement. This research focuses on 30 life histories of older people in Santiago, Chile. They were asked about their histories and SSNs. The analysis applied used a Qualitative Comparative Analysis (QCA) with conditions from the Social Network Analysis (SNA). The results identify sufficient and necessary conditions to achieve satisfaction with retirement. It is highlighted some of the dimensions of SSNs and their reciprocities as relevant conditions for satisfaction with retirement.
</abstract>

Satisfaction with Retirement: A Qualitative Comparative Analysis with Social Network Analysis

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Variationist studies have shown the implication of tie properties in the emergence and preservation of linguistic norms. This contribution deepens the understanding of this mechanism at the dyadic level. It explores relational subjectivity and relativity among individuals of a community and their implications in the distribution of lexical variants. The aim is to understand how the reciprocity of a relation influences the share of lexical practices. To do so, we analyze the network of discussions of bachelor's degree students of the University of Geneva and their lexical practices. Using the modern methods used in social network analysis to study relational properties and by running multiple regression quadratic assignment procedure (MRQAP), reciprocal interactions are found to lead to a higher lexical share and similarity.
</abstract>

On the Effect of Reciprocal Dyadic Relations on the Share of Lexical Practices

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The fields of social network analysis and network science have recently undertaken efforts to address issues of gender diversity and representation. However, despite these important efforts, subtle threats to representation are likely to persist. I use a 2023 global survey of 260 network researchers to show that men rate themselves as having more expertise with networks than women. This is troubling because, to the extent that women believe they lack the expertise to be considered for awards or collaboration opportunities, it can impede other efforts to diversify the field. I conclude by discussing some possible explanations for this finding and some possible strategies for addressing its consequences.
</abstract>

Men Think they Know More about Networks

AHEAD OF PRINT

Volume 44 (2024): Issue 1 (January 2024)

Volume 43 (2023): Issue 1 (January 2023)

Volume 42 (2022): Issue 1 (January 2022)

Volume 41 (2021): Issue 1 (January 2021)

Volume 40 (2020): Issue 1 (January 2020)

Volume 39 (2019): Issue 1 (January 2019)

Volume 38 (2018): Issue 1 (January 2018)

Volume 37 (2017): Issue 1-2 (January 2017)

Volume 36 (2016): Issue 1 (January 2016)

Connections

Connections publishes original empirical, theoretical, and methodological articles, as well as critical reviews dealing with applications of social network analysis. From volume 2018 the journal is published in a continous format.  The research spans many disciplines and domains including: Anthropology, Sociology, Psychology, Communication, Economics, Organizational Behavior, Knowledge Management, Marketing, Social Psychology, Mathematics, Public Health, Medicine, Computer Science, and Policy.  As an official journal of the International Network for Social Network Analysis, the emphasis of the publication is to reflect the ever-growing and continually expanding community of scholars using network analytic techniques. Connections also provides an outlet for sharing news about social network concepts and techniques and new tools for research.  Rejection rate: 60%  Open Access Policy  This journal provides immediate open access to its content under the Creative Commons CC BY 4.0 license on the principle that making research freely available to the public supports a greater global exchange of knowledge. Under the Creative Commons CC BY 4.0 license users are free to share (copy and redistribute the material in any medium or format) and adapt the work (remix, transform, and build upon the material for any purpose, even commercially) if the contribution was properly attributed and all of the changes indicated.  ABOUT SOCIETY  International Network for Social Network Analysis is the professional association for researchers interested in social network analysis. The association is a non-profit organization incorporated in the state of Delaware and founded by Barry Wellman in 1977.  INSNA was founded on the premise that the behavior and lives of social entities are affected by their position in the overall social structure. By examining the etiology and consequences of structural forms overall, of the location of entities within these structures, and of the formation and dynamics of ties that make up these structures, INSNA hopes to learn about the parts of behavior that are uniquely social.  Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process.

Connections

Volume 43 (2023): Issue 1 (January 2023)

Satisfaction with Retirement: A Qualitative Comparative Analysis with Social Network Analysis

On the Effect of Reciprocal Dyadic Relations on the Share of Lexical Practices

Men Think they Know More about Networks

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