Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Investigar sobre lo que ocurre en Internet frecuentemente nos aproxima a estudios que se sitúan en la frontera del conocimiento. Este artículo se enmarca en el espacio transdisciplinar de las Ciencias Sociales y Sociología Computacionales con el objetivo de presentar el desarrollo actual de la investigación que toma como referencia Social Big Data o datos sociales masivos, describir procesos metodológicos que son típicos en este campo donde los medios sociales en Internet son la fuente principal de datos y, al hilo de esta descripción, destacar algunas de las ventajas, limitaciones y desafíos para la investigación en este campo, muy ligados a los avances metodológicos y técnicos que se hacen en otras ciencias. El texto introduce la especificidad conceptual de los Social Big Data como confluencia de los medios sociales, análisis de datos y datos masivos. Se explora qué cambios suponen los procesos de investigación en este campo y se exponen avances en el trabajo con datos sociales masivos en áreas de la inteligencia artificial como el aprendizaje automático, las redes neuronales artificiales o el aprendizaje profundo, que se alinean con unas ciencias sociales que tienden a la predicción. Argumentamos a continuación sobre la pertinencia para la Sociología, así como para otras ciencias, de avanzar igualmente en un enfoque basado en métodos mixtos en el campo de los Social Big Data, repensando el vínculo micro – macro en este campo de estudio. A través de un estudio de caso que intercalamos (sobre las expresiones en Twitter del movimiento negacionista en España que se produce al hilo de la pandemia de COVID-19), ilustramos igualmente algunas potencialidades y limitaciones de este tipo de investigación, lo que nos permitirá esbozar algunos de los desafíos metodológicos que pueden incorporarse en una agenda de investigación en esta área. Un área de investigación que ofrece direcciones de gran interés para la sociología en los próximos años y en la que se puede avanzar de manera excepcional en el desarrollo de la transdisciplinariedad y la hibridación en lasCiencias, enriqueciéndolas. The research on what happens on the Internet often brings us closer to studies at the frontier of knowledge. This article is part of the transdisciplinary space of  Computational Sociology and Social Sciences. It pretends to present the current development of research referred to as Social Big Data. It describes methodological processes typical in this field where social media on the Internet are the primary data source. Along with this description, it highlights some of the advantages, limitations, and challenges for research in this field, closely linked to methodological and technical advances made in other sciences. The text introduces Social Big Data's conceptual specificity as a confluence of social media, data analysis, and massive data. Then, we explore essential changes in the research process in this field and advances in working with social big data in areas of artificial intelligence such as machine learning, artificial neural networks, and deep learning, which are aligned with social sciences that tend to predictions. We then argue about the relevance for Sociology and other sciences to advance in an approach based on mixed methods in the Social Big Data area, rethinking the micro-macro link in this field of study. Through a case study [on the negationist social movement in Twitter in Spain during the COVID-19 pandemics], we also illustrate some potentials and limitations of this type of research, which will allow us to outline some of the methodological challenges that experts could incorporate into a research agenda in this area. Social Big Data and Computational Sociology and Social Sciences research offer directions of great interest to the Sociology of the coming years in which exceptional progress can be made in the development of transdisciplinarity and hybridization in science, enriching them.

For more than twelve years (2006-2018) we developed four consecutive research projects of the Spanish National R&D&I Plan on binational couples with one Spanish member. Our objective was to study gender relations and interculturality management in a broad sample of national combinations and spatial and biographical contexts. In this article we present the methodological process and decision making adopted during these four projects, highlighting their innovative aspects. Our aim is to explain what was intended in each of these projects, how the objectives were achieved and why the related methodological decisions were made. The article is structured in two large sections. The initial one presents the objectives pursued for the first three projects and justifies the pertinence of adopting a qualitative methodological approach. The relevant use of two privileged techniques for data collection during these projects is also highlighted: the in-depth interviews, on the one hand, and the observation on the other hand. The last one was carried out in observation units corresponding to some of the foreign spouses’ places of origin (various areas of Brazil, as well as Mexico City and Kiev). The second section deals with the design developed for carrying out a non-initially planned Longitudinal Qualitative Research (LQR), based on a selected sample of couples interviewed throughout the first three studies. We present the crucial issues and the decision making associated to the required methodological design, focused on the questions that arose both for the conformation of the sample and for the realization of the interviews. Lastly, the article addresses the following question: how is it possible to carry out longitudinal qualitative research based on projects not initially proposed as such and within the framework of a National Research Plan?

In this work, the interaction between sport, eating practices, and body control are studied in four-generation Spanish female athletes, in all of them, three degrees of sport intensity are distinguished, from professional to amateur. A socio-historical approach is used, which allows us to see the process of the social construction of the body, since the post-civil war, when sports activity is experienced by women as a leisure activity and surrounded by food deficiencies, to today, where the performance has modified dietary patterns to achieve sports goals. It will also make visible the way in which dietary practices, body control, and sports norms are integrated into the daily life of women, even without being professional athletes. This work, carried out through qualitative research with in-depth interviews, shows how sports, food and body practices have altered over time, as well as their determinants, which are modified generationally. If in the first generation the material context is the one that determined the practices, during the stage of modernization, the situation is reversed. As the sports dimension takes centre stage and is integrated into the daily practices of women, it is observed how the processes of body construction are modified that are accompanied by changes in sports and eating behaviours.

The growing importance of the field of the collaborative economy is associated with the growth of the technological platforms that develop their business model in this sector. These companies occupy a central position in this space and accumulate more and more power to define the space of possibilities of the practices that fit in the collaborative economy. Of all of them, the European company Blablacar seems to occupy a privileged place in this sector. His position is reinforced by a discourse steeped in collaborative rhetoric. This factor, the speech, is a hallmark of these companies. Its objective is to try to frame the business model in a different space from that of more conventional capitalism. However, our analysis of this discourse allows us to identify philosophical and ideological assumptions far removed from altruistic values. On the contrary, it induces a series of surveillance tasks between users to be carried out. Second, the analysis by means of virtual ethnography of its reputation systems allows us to point out the importance of the hidden work on which the sector is sustained. The different dimensions of this hidden work are analyzed. Finally, it is suggested the need, if rigor is to be preserved, to stop using any reference to the term collaborative in the analyzes of this platform or of others based on similar conditions.

Social Network Analysis (SNA) is an increasingly applied tool in sociological research and, particularly, in migration studies. Nevertheless, it has been used only for contemporary migrations up to now, lacking its presence in history of migration, which demands new methodological approaches. Accordingly, SNA has been used for the social assessment of the migrant Irish community settled down in early modern Biscay, fleeing from the English rule. The analysis has been based on dataset built from different historical archives and covering a wide range of information –familiar, trade, business, etc. Networks arising from these different archives have been both individually treated and collectively in an aggregate way, leading to successful results based on this methodological approach. The research has provided a detailed description of the Irish community in Biscay, pointing out its structure and functioning, areas and mechanisms of interaction, most noteworthy actors within the network, and other minor issues.