This article pays tribute to Jose Luis Molina, Professor of Social Anthropology at the Universitat Aut & ograve;noma de Barcelona, whose work has been decisive in the development and expansion of social network analysis in Latin America. Over more than three decades, his interdisciplinary approach has influenced fields such as migration, the informal economy, mutual aid, and new forms of digital work. But his legacy transcends the scientific: he has been a mentor, a driving force behind academic communities, and a key figure in the creation of international collaborative networks. This text gathers the voices of colleagues, disciples, and friends from Europe and Latin America who bear witness to his generosity, critical vision, and ethical commitment. It also includes a visual analysis of his co-authorship network. Gathered on the occasion of an academic meeting in Le & oacute;n (July 2025), these texts pay tribute to a natural leader who has masterfully woven a dense network of relationships.
This article examines the narratives of the anti-mask movement by analyzing the evolution of the conversation about "muzzles" and masks on Twitter, comparing three time periods (2020-2023), and paying special attention to the Spanish case. While social science research on the pandemic is prolific, little attention has been given to the study of semantic networks. This work is based on data collected by the NON-CONSPIRA-HATE! Project (Conspiracy Theories Dataset, 2020-2023), comprising 5,509,549 organic tweets, from which a Spanish-language subsample of 556,549 tweets discussing muzzles, masks, and equivalent terms was collected. The temporal evolution of the discourse on masks was analyzed through tokens, mentions, hashtags, their co-occurrence networks (co-mentions, cohashtags), community affiliations, and sentiment and emotion analysis. The study highlights the narrative prominence of the term "muzzle" within the anti-mask movement, as well as the diversity of co-mentions and co-hashtags networks, with both local and global actors, mentions, and narratives standing out. The latter demonstrate their centrality in the conspirative discourse within the Spanishspeaking sphere. In the case of Spain, the findings reveal significant distrust toward public authorities, strong criticism, and even anger directed at political leaders across the ideological spectrum, along with attacks on the media.
The scientific production of various fields of knowledge can be explored through scientometric approaches such as bibliometrics and disciplines such as the sociology of science. The present study explores the academic networks that make up the scientific production of the field of ethnomusicology. Using concepts such as social capital and methodologies such as bibliometrics and social network analysis (SNA), this study explores the co-occurrence networks of key terms, the documents with the most citations globally, collaborative networks, institutions, countries, authors, co-authorship, and the main disciplinary approaches involved in contemporary ethnomusicological studies. From the creation of a bibliographic corpus extracted from two determinant bibliographic information bases in contemporary science studies; Scopus and Web of Science, several networks are modelled, and the corresponding bibliometric indicators are established. The results present different disciplinary approaches, authors' keywords, abstract analysis and the main scientific fields that converge in contemporary ethnomusicology. Some technological and conceptual implications of contemporary science are discussed with respect to the future of the study of music and ethnomusicology.
The emergence of the giant component in networks has been a topic of study, spanning classical random graph models to more recent developments in network analysis. However, in the case of citation networks among scientific articles, it remains unclear whether the evolution of the largest components exhibits a phase transition, like models or other types of networks. If it does, it is uncertain whether indicators derived from these models can help identify the emergence of the giant component. This paper analyses the evolution of the largest component in the citation networks of five journals published by the American Physical Society: PRA, PRB, PRC, PRD, and PRE. The first four journals have data spanning over 40 years, while PRE has data for 20 years. The study finds that the five networks exhibit a phase transition similar to the Erd & ouml;s-Renyi model, and the indicators derived from this model are more effective than others in identifying the emergence of the giant component. Additionally, it demonstrates that the phase transition can be modelled using logistic regression, which provides another potential indicator for identifying the emergence of the giant component.
Complex sociobiological systems, such as those established between birds and trees, are characterized by the exchange and distribution of information/energy through social interaction processes under stochastic conditions. While this particularity makes tracing these exchanges virtually impossible at the system-wide level, this networking represents an indicator of the system's level of organization and sustainability. Social network analysis was decided to be used in order to express these links, with the objective of identifying part of this social complexity established at a given organizational level between the avifauna and flora of a particular region. The willingness of birds to locate certain trees allowed us to suggest social affiliation actions, generate a bimodal adjacency matrix, measure these links, and allow us to observe specific actors, trees and birds, as key players in the concentration and/or transmission of information. It also allows us to hypothesize, collaterally, a vulnerability angle for the system itself. The disappearance of any of these species would impact the biotic and energetic framework of the forest. This could contribute as a tool in habitat management, highlighting the importance of analyzing and preserving the diversity and cohesion of a network of biotic interactions between different species.
This paper analyzes articles published in REDES. Hispanic Journal for the Analysis of Social Networks, which used SNA (Social Network Analysis) to study different aesthetic practices. It covers eleven papers in relation to arts, crafts and design written by twenty authors from four countries. In each article, five dimensions were investigated: 1) the themes and methodological approaches, 2) the cited bibliography, 3) the central concepts used, 4) the importance that ARS acquired in the academic careers of the authors and 5) the links between the authors of these articles. It is concluded that the use of social network analysis for the study of aesthetic practices remains an underexplored area of research, and that the twenty authors mentioned are part of a quasi-group with common interests.
In small-scale agriculture, the producer's relational position-their social capital-can be as decisive as their resources when it comes to decision-making and innovation. Using a social network analysis approach, this study analyzes how social capital configurations-bonding, bridging, and linking- influence the level of innovation adoption among small-scale maize producers in Mexico. With a sample of 28,233 producers distributed across 16 states, the study analyzes socioeconomic variables -age, on-farm consumption share, planted area, buyers- and productive variables -Innovation Adoption Index (InAI), grain yield-; as well as the network metric of normalized radiality. The main findings show an upward trend in innovation adoption, yield, and normalized radiality as different forms of social capital are combined. Notably, producers who simultaneously integrate all three forms achieve the highest medians (p < 0.05) for InAI (27%), yield (3 t ha-1), and normalized radiality (0.08). These findings suggest that the diversity and complementarity of social ties-from strong community bonds to connections with institutional and market actors-function as enabling mechanisms for innovation, productivity, and market integration, offering a promising pathway for designing extension policies and strategies based on agricultural innovation systems.
Disinformation represents one of the main challenges for modern democratic societies, affecting freedom, coexistence, and social trust, as became evident during the Covid-19 pandemic. Informational disorders and polarization are interconnected phenomena that worsen social fragmentation, intensified by the role of social networks and artificial intelligence algorithms, which reinforce echo chambers online and the most extreme and polarizing discourses. This special issue presents five case studies in Spain that analyze different social consequences of these processes: the influence of the media on digital polarization, the proliferation of conspiracy theories, the spread of hate speech, and digital inequality in political participation. The volume also includes reviews of three books that address the challenges of disinformation, the role of artificial intelligence, and journalistic verification. This introduction concludes with a reflection on the challenge faced by social scientists in understanding these dynamics and attempting to mitigate their harmful effects. For this purpose, Social Network Analysis (SNA) and new computational methodologies supported by artificial intelligence are extremely useful.
This research addresses the polarization on Twitter/X during the 28-M 2023 elections in Spain, focusing on the influence of the media on the digital conversation. The sample includes 1,186,906 tweets downloaded with the platform's academic API, filtered and analyzed using qualitative and quantitative techniques and network analysis, which have been visualized with graphs created with Gephi to highlight the interactions generated around ten representative media: Abc, elDiario.es, El Confidencial, El Mundo, El Pais, El Peri & oacute;dico, La Raz & oacute;n, La Vanguardia, Okdiario and P & uacute;blico. The results reveal differences in the organization of progressive and conservative communities, the latter being more centralized and hierarchical compared to progressive dispersion. In addition, symmetric and asymmetric polarization dynamics are identified, depending on the topic in question. Three case studies of different magnitude and political significance have been analyzed, in addition to the general sample. It is concluded that digital native media play a key role in the polarization and viralization of content, with respect to traditional media, highlighting their ability to influence public conversation and amplify specific stories in the digital ecosystem.
Social networks have become ideal platforms for the propagation of hate speech. However, they also offer opportunities for the dissemination of counter-narratives, which seek to challenge and counter these expressions of hate. This study analyses the dynamics of hate speech and counter-narratives on Twitter (now X) following the attack on Catholic churches in Algeciras, Spain, in 2023, perpetrated by a Muslim migrant. Using a dataset of over 350,000 tweets, we use Gephi to construct and analyse retweet networks, uncovering structural and dynamic differences between communities that propagate hate and those promoting counter-narratives. In the results we identify and characterise five different types of communities (one counter-narrative and four hate communities). Hate communities are denser and more cohesive, with influential users playing a central role in amplifying content. However, the harshness of the discourse and characteristics of the network members will also play a role. Counter-narrative networks, while less cohesive, show potential to reach diverse audiences. Polarisation emerges as a key challenge, with minimal interaction between opposing communities, reinforcing echo chambers and limiting the effectiveness of counter-narratives.
The present study aims to analyse the evolution of hate speech in contexts of war and truce in the armed conflict between Israel and Hamas. To this end, content analysis and social media tools are used to identify patterns and changes in public perception of the sides involved. Three key periods of the conflict were analysed: from 7to 28 October 2023 (first period); from 24 November to 1 December 2023 (second period); and from 28 February to 6 March 2024 (third period). The research used software such as Atlas.ti 24 for content analysis, Gephi for structural analysis of social networks, and Easy Web Data Scraper for automated collection. In total, 351 tweets were collected and processed with artificial intelligence using Perplexity, which allowed for the identification of repeated words associated with hostile speech. The results indicate a significant decrease in hostile messages between the war and truce periods.
The interest in documenting what happens to various populations in retirement has given way to consider little-explored groups such as priests; related retirement studies take up transcendental elements like economics, coping strategies and inclusion in new activities. The aim of this paper was to describe the social disengagement process of a group of retired Catholic priests. The research was descriptive with a phenomenological orientation, seeking to understand the changes perceived upon retirement as well as the meanings given to the experience through an interview whose guiding question was: What changes do you recognize you have experienced since retiring from your priestly activities? The results outline the experience of withdrawal in three stages: starting to disengage, maintaining disengagement, and complete disengagement. It is clear that this process happens slowly and is connected to health issues and staying away from social and religious activities. It is concluded that disengagement is a process related to the severance of ties and coping methods, both of which provide insight into the social aspects of self-perceived ageing in retirement.
The promotion of bio-resources in areas with high rates of deforestation and transition to legal crops has increased in recent years in Colombia. However, these have been analyzed using traditional value chain models that prevent us from understanding the dynamic relationships between actors, socioecological components, and the possibility of reducing impacts on the ecosystems from which these resources originate. This research analyzes the perspective of socio-ecological value networks, focusing on the study of stakeholder relationships and interdependencies in order to understand how they affect decision-making within the value network in Guaviare, Colombia. This is done through the analysis of quantitative and qualitative data derived from surveys, interviews, and participatory workshops. This study combines social network analysis to create an approach that allows for a deeper understanding of: 1) the relationships between and within the productive links, 2) the structure of the socio-ecological system involved in the network, and 3) the statistical differences between levels of centrality. It concludes that value networks represent a relevant reticular and structural approach to addressing the problem of deforestation on the southern edge of the Colombian Amazon.
This study aims to propose a measurement model of social capital in artisan communities engaged in textile activities through a confirmatory factor analysis (CFA) applying the structural equation modeling (SEM) approach. Social capital is understood as a multidimensional construct composed of three dimensions: social networks, collective action, and trust. The methodological design is quantitative, non-experimental, cross-sectional, and correlational, using a structured instrument applied to a simple random sample of 354 artisans. Exploratory factor analysis was employed to identify the latent structure of the construct, confirmatory factor analysis to assess convergent and discriminant validity, and a structural equation model to verify the model's fit. The overall model fit indices were satisfactory, with a chi-square of 82.994 and an RMSEA of 0.105, while incremental and parsimony fit indices also reached optimal levels, above .900 and below .600 respectively, supporting the proposed factorial structure. The SEM confirmed the theoretical relationships between the dimensions, validating their conceptual interdependence as essential components of social capital. This analysis contributes to the field by proposing an empirically validated measurement model of social capital adapted to the specific context of artisan communities.
This research has a twofold objective: first, to determine in which grade the themes of scientific ethics and academic integrity have been expressed on Twitter/X; second, to reveal and delve deeper into the topics generated around those central themes and, with this, to analyse the dynamics of the main users who are involved in them. To this end, a database was set up with just over 201 thousand tweets that used at least one of the 22 defined terms and related to the core themes. The fundamental unit of analysis was the hashtags that are used on the tweets. Besides, the social network analysis approach was applied to reveal and understand how they are linked to each other. The results show that the scientific ethics theme is well-represented on Twitter; also, a great diversity of hashtags has been used, which shape different thematic strands, one of which is strongly related to artificial intelligence. Additionally, the users have distinct roles related to the hashtags. It is concluded showing that Twitter is a good space for the expression of scientific ethics; nevertheless, there are both positive and negative strands regarding this.
In December 2021, the Spanish Minister of Consumer Affairs made statements to the newspaper The Guardian that sparked a heated debate on social networks about Spanish macro farms. This article addresses the analysis of Twitter messages regarding this phenomenon that led to debates co-opted by political leaders, who centralized public opinion. The database is made up of 339,901 messages downloaded on the network during two weeks in January 2022. The messages have been analyzed using "Social Network Analysis" techniques: machine learning algorithms and sentiment analysis dictionaries to investigate the levels of negativity presented by the published messages. The main results point to elitist and non-inclusive communication strategies in some of the parties and others that are more egalitarian, with themes that focus mainly on the protection of "livestock farmers" against the issue of the climate emergency.
Los sistemas complejos sociobiológicos, como el establecido entre aves y árboles, se distinguen por el intercambio y distribución de información/energía a través de procesos de interacción social bajo condiciones estocásticas. Si bien dicha particularidad hace prácticamente inaccesible el rastreo de dichos intercambios a nivel de todo el sistema, esta reticularidad supone un indicador del nivel de organización y sostenibilidad del mismo. Se decidió expresar dichas vinculaciones utilizando el análisis de redes sociales, con el objetivo de identificar parte de esta complejidad social establecida en un nivel organizativo determinado entre la avifauna y flora de una región en particular. La disposición de aves a situarse en determinados arboles permitió sugerir acciones de afiliación social, generar una matriz bimodal de adyacencia, medición de dichas vinculaciones, la posibilidad de observar determinados actores, árboles y aves, nodales en la concentración y/o transmisión de la información, así como suponer, colateralmente, un ángulo de vulnerabilidad del propio sistema. La desaparición de alguna de estas especies implicaría la afectación del entramado biótico y energético de la floresta. Esto podría contribuir como herramienta en la gestión de hábitats destacando la importancia de analizar y preservar la diversidad y cohesión de una red de interacciones bióticas entre diferentes especies.
La estructura de relaciones sociales juega un papel crucial en el aprendizaje, difusión de innovaciones y construcción de capital social en la agricultura, tanto al interior de las comunidades (bonding) como al exterior (bridging y linking), por lo cual, es deseable construir este tipo de vínculos. El objetivo fue analizar el patrón de los vínculos sociales de los productores y su influencia en la gestión del capital social, la adopción de innovaciones y su impacto en la producción agrícola. Se aplicó una encuesta a 28,233 productores de maíz en México. Se construyeron redes de aprendizaje mediante matrices de afiliación y se calculó el indicador de nodo de radialidad. Los hallazgos revelaron que solo el 3% de los productores gestionan efectivamente las tres formas de capital social (bonding, bridging y linking) obtienen rendimientos superiores al promedio (p ≤ 0.05) de hasta 1.8 t ha-1, en comparación con aquellos que no reportan acceso a ninguna forma de capital social. Además, se identificó una asociación positiva entre la adopción de innovaciones y las distintas formas de capital social. Se concluye que en la extensión agrícola debe fomentar la construcción de capacidades relacionales para mejorar la gestión en la producción agrícola.
En la era digital, las redes sociales han amplificado la difusión de teorías conspirativas y discursos de odio, especialmente en contextos como la pandemia de COVID-19, la migración y los debates sobre diversidad de género. Este estudio analiza cómo estas narrativas tóxicas se han construido y propagado, exacerbando la polarización social. Durante el COVID-19, las teorías conspirativas proliferaron, atribuyendo falsamente el origen del virus a armas biológicas o planes de control poblacional, lo que desencadenó desinformación masiva y discriminación hacia grupos específicos. En paralelo, los migrantes fueron señalados como amenazas sanitarias y económicas, reforzando estigmas y xenofobia mediante campañas digitales que explotaron sesgos cognitivos. Respecto a la diversidad de género, los discursos conservadores intensificaron su oposición a los derechos LGBTIQ+, utilizando desinformación para alimentar divisiones sociales. El análisis revela un patrón común: la instrumentalización del miedo y la incertidumbre para construir enemigos imaginarios. Este fenómeno subraya la necesidad de contrarrestar estas narrativas con estrategias basadas en datos verificables y educación digital crítica.
La producción científica de diversos campos del conocimiento puede ser explorada mediante enfoques propios de la cienciometría como la bibliometría y disciplinas como la sociología de la ciencia. El presente estudio explora las redes académicas que componen la producción científica del campo de la etnomusicología. A partir de conceptos como capital social y metodologías como la bibliometría y el análisis de redes sociales (ARS), este estudio explora las redes de co-ocurrencia de los términos clave, los documentos con más citaciones de modo global, las redes de colaboración, instituciones, países, autores, coautoría y los principales enfoques disciplinares que participan en los estudios etnomusicológicos contemporáneos. A partir de la creación de un corpus bibliográfico extraído de dos bases de información bibliográfica determinantes en los estudios de la ciencia contemporánea; Scopus y Web of Science, se modelan diversas redes y se establecen los indicadores bibliométricos correspondientes. Los resultados presentan diversos enfoques disciplinares, palabras clave de autores, análisis de resúmenes y los principales campos científicos que confluyen en la etnomusicología contemporánea. Se discuten algunas implicaciones tecnológicas y conceptuales de la ciencia contemporánea respecto al devenir del estudio de la música y la etnomusicología.
