Abstract: 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. PubDate: Fri, 10 Mar 2023 00:00:00 GMT
Abstract: 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. PubDate: Tue, 28 Feb 2023 00:00:00 GMT
Abstract: This brief article illustrates the features of ScriptNet, a software package that facilitates a visual analysis of the organisational aspects of criminal enterprise, together with a visual analysis of the network of people, organisations, places and resources that are in some way involved in the commissioning of these goal-oriented crimes. ScriptNet is an amalgamation of the terms ‘script’ and ‘network’ that in turn represent two analytical approaches to understanding criminal and social behaviours. Script refers to crime script analysis, an analytical technique that organises knowledge about the procedural aspects and procedural requirements of the crime commission process. Network derives from social network analysis, and specifically from the framework of multi-mode and multi-link networks, which maps individual and collective actors, together with resources they can access and places where they are located, and the various types of relationships that may link them. In this article we illustrate the functions and features of ScriptNet using data provided by the Food Safety Authority of Ireland (FSAI). We discuss the innovative aspects of ScriptNet and we identify its limits. In its current format, ScriptNet has been developed as proof of concept. The code is open source, and we welcome people to collaborate and implement new and improved functions. PubDate: Fri, 28 Oct 2022 00:00:00 GMT
Abstract: Isolation and cohesion are two key network features, often used to predict outcomes like mental health and deviance. More cohesive settings tend to have better outcomes, while isolates tend to fare worse than their more integrated peers. A common assumption of past work is that the effect of cohesion is universal, so that all actors get the same benefits of being in a socially cohesive environment. Here, we suggest that the effect of cohesion is universal only for specific types of outcomes. For other outcomes, experiencing the benefits of cohesion depends on an individual’s position in the network, such as whether or not an individual has any social ties. Network processes thus operate at both the individual and contextual level, and we employ hierarchical linear models to analyze these jointly to arrive at a full picture of how networks matter. We explore these ideas using the case of adolescents in schools (using Add Health data), focusing on the effect of isolation and cohesion on two outcomes, school attachment and academic engagement. We find that cohesion has a uniform effect in the case of engagement but not attachment. Only non-isolates experience stronger feelings of attachment as cohesion increases, while all students, both isolates and non-isolates, are more strongly engaged in high cohesion settings. Overall, the results show the importance of taking a systematic, multi-level approach, with important implications for studies of health and deviance. PubDate: Fri, 28 Oct 2022 00:00:00 GMT
Abstract: Political network data can often be challenging to collect and clean for analysis. This article demonstrates how the incidentally and backbone packages for R can be used together to construct networks among legislators in the US Congress. These networks can be customized to focus on a specific chamber (Senate or House of Representatives), session (2003 to present), legislation type (bills and resolutions), and policy area (32 topics). Four detailed examples with replicable code are presented to illustrate the types of networks and types of insights that can be obtained using these tools. PubDate: Fri, 14 Oct 2022 00:00:00 GMT
Abstract: Hairball buster (HB) (also called node-neighbor centrality or NNC) is an approach to graph analytic triage that uses simple calculations and visualization to quickly understand and compare graphs. Rather than displaying highly interconnected graphs as ‘hairballs’ that are difficult to understand, HB provides a simple standard visual representation of a graph and its metrics, combining a monotonically decreasing curve of node metrics with indicators of each node’s neighbors’ metrics. The HB visual is canonical, in the sense that it provides a standard output for each node-link graph. It helps analysts quickly identify areas for further investigation, and also allows for easy comparison between graphs of different data sets. The calculations required for creating an HB display is order M plus N log N, where N is the number of nodes and M is the number of edges. This paper includes examples of the HB approach applied to four real-world data sets. It also compares HB to similar visual approaches such as degree histograms, adjacency matrices, blockmodeling, and force-based layout techniques. HB presents greater information density than other algorithms at lower or equal calculation cost, efficiently presenting information in a single display that is not available in any other single display. PubDate: Fri, 28 Feb 2020 00:00:00 GMT
Abstract: In order to understand scientists’ incentives to form collaborative relations, we have conducted a study looking into academically relevant resources, which scientists contribute into collaborations with others. The data we describe in this paper are an egocentric dataset assembled by coding originally qualitative material. It is 40 multiplex ego networks containing data on individual attributes (such as gender, scientific degree), collaboration ties (including alter–alter ties), and resource flows. Resources are coded using a developed inventory of 25 types of academically relevant resources egos and alters contribute into their collaborations. We share the data with the research community with the hopes of enriching knowledge and tools for studying sociological and behavioral aspects of science as a social process. PubDate: Fri, 28 Feb 2020 00:00:00 GMT
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