<p>El presente ensayo se enfoca en identificar posibles aportes del análisis de redes sociales (ARS) al análisis de la estructura social.  Se examina la potencial contribución de las perspectivas reticulares para delimitar una estructura social y describir su evolución. Para ello se abordan conceptos de Luhmann (y sus intercambios con la teoría de los sistemas de acción social de Parsons) desde la perspectiva sistémica, y de la teoría de estructuración social de Giddens. No se incluye el abordaje de la estructura social desde la teoría marxista en este ensayo, dado que ello implicaría una revisión teórica exhaustiva que excede su objetivo.  Se exponen algunas ventajas de la noción de “redes sociales” para el estudio de la estructura social en forma complementaria al uso de las técnicas atributivas clásicas de la sociología empírica moderna. Para este desafío se proponen indicadores, métricas, modelos de redes aleatorias y topologías ARS. Se considera que el abordaje empírico y el teórico permiten un <em>corpus </em>integrado para la conceptualización y la investigación de la estructura social. La aplicación del <em>network thinking</em> para examinar la estructura social resulta en cierta forma original, pues es un enfoque que se ha utilizado más frecuentemente para analizar la dinámica de ciertos agentes o grupos dentro de la sociedad.<strong></strong></p>Se concluye que la confluencia del ARS con algunas nociones teóricas de la teoría de sistemas sociales es útil para el análisis de la estructura social, conceptualizada como patrones dinámicos de intercambios reales y potenciales entre individuos humanos en formato de redes.

Big data stream analytics platforms not only need to support performance-dictated elasticity benefiting for instance from Cloud environments. They should also support analytics that can evolve dynamically from the application viewpoint, given data nature can change so the necessary treatments on them. The benefit is that this can avoid to undeploy the current analytics, modify it off-line, redeploy the new version, and resume the analysis, missing data that arrived in the meantime. We also believe that such evolution should better be driven by autonomic behaviors whenever possible. We argue that a software component based technology, as the one we have developed so far, GCM/ProActive, can be a good fit to these needs. Using it, we present our solution, still under development, named GCMstreaming, which to our knowledge seems to be quite original.

This paper presents the results of a research-action project carried out in Rivera (Uruguay) and the Binational Conurbation that integrates with Livramento (Brazil). The research aimed to strengthen a university region in this Conurbation, a pole of attraction for students from various adjacent areas. The study analyzes the institutional relations in the higher education system between 2020 and 2021 and proposes actions that can become territorial economic development. Relevant actors were identified through in-depth interviews. The actors analyzed are institutional (universities, trade and business associations, municipalities, and others). These actors are then interpreted as nodes of an institutional network through social network analysis (SNA) using Gephi software. Relationships between the institutions of the higher educational system in Rivera were identified (for example, joint careers, agreements, and research). The nodes were georeferenced (using GeoLayout), creating a dynamic institutional mapping. However, both in the local imaginary and the discourse of the authorities, Rivera and Livramento must work to consolidate themselves as a university region. In this research, it was observed that there are still no complete and agreed strategic lines in this regard. In this sense, the application of social network analysis also makes it possible to think about and encourage the application of public policies from a network and collaboration perspective between institutions to achieve complex community objectives.

This article links the theory of social structuring and the SNA (Social Network Analysis). We understand the emergence of religious networks as a more general process of social structuring. In the processes of structuring social networks, the connections are no longer random and become hierarchical and preferential links. Social structuring is associated with the models of random networks (ER); the greater or lesser degree of structuring, is a greater or lesser degree of randomness in the structuring of social ties. The concepts of real and potential connections are addressed, and ARS models are applied to the characterization of monotheism and polytheism. The nature of religious ties and normative networks is specified. Isomorphism of social structuring in politics and religion, and inter-religious conflict, are addressed.

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