(English below)Esta investigación estudia las características de los comentarios que logran más impacto en un entorno digital. Se emplea una metodología cualitativa que analiza los 50 mensajes con más likes del foro de una noticia, publicada en Marca.com, en la que el jugador del Real Madrid Vinicius Junior denuncia los episodios racistas sufridos en los estadios de fútbol españoles. Se tienen en cuenta las emociones expresadas por los autores, así como las estrategias retóricas y argumentales utilizadas en los comentarios. Se concluye que los mensajes escritos con empatía, aunque estén en contra de la opinión mayoritaria, pueden tener cierto impacto si formulan un argumento dual que reconoce las opiniones contrarias como valiosas en algún punto, incluso sin validarlas. En el análisis de la eficacia de los mensajes se observa que lo distinto se premia, como aportar un dato inesperado de forma inteligente (ironía) o presentar una opinión contraria a lo que se espera por pertenecer a un determinado grupo (afiliación):en este último caso el comentario resulta más auténtico y, por lo tanto, es más impactante. Se demuestra también que la percepción de los mensajes es compleja y que algunos elementos o rasgos que habitualmente se consideran eficaces pueden no serlo. Así sucede con los comentarios breves, que no siempre tienen trascendencia y pueden aparecer como inconsistentes si no incluyen una argumentación. Tampoco la diversidad o la acumulación de argumentos es positiva en cualquier circunstancia: compensa más usar los argumentos por separado para no distraer del objetivo persuasivo. This research examines the characteristics of comments that achieve the greatest impact in a digital environment. A qualitative methodology is used to analyse the 50 most liked messages in the forum discussion prompted by a news article published on the Spanish sports newspaper Marca.com. The article focuses on Real Madrid player Vinicius Junior’s denunciation of racist incidents in Spanish football stadiums. This study considers the emotions expressed by the authors, as well as the rhetorical and argumentative strategies employed in the comments. The findings suggest that messages written with empathy, even when opposing the opinion of the majority, can have a significant impact if they present a dual argument that acknowledges opposing views as valuable in some respects, even without validating them. The analysis reveals that originality is rewarded, such as introducing an unexpected fact in an intelligent manner (e.g., irony) or expressing an opinion contrary to expectations based on group belonging (affiliation). In the latter case, the comment appears more authentic and, therefore, more impactful. The study also demonstrates that the perception of messages is complex, and some elements traditionally considered effective may not always be so. For example, brief comments do not always carry weight and can come across as inconsistent if they lack sufficient argumentation. Similarly, the diversity or accumulation of arguments is not universally positive; it is often more effective to present arguments separately to avoid distracting from the persuasive objective.
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In an image-saturated society, methods for visual analysis gain urgency. This special issue explores visual ways to study online images, focusing on their collection and circulation. The proposition we make is to stay as close to the material as possible. How to approach the visual with the visual? What type of images may one design to make sense of, reshape, and reanimate online image collections? How may arrangements of online images promote various analytical procedures, participatory actions, and design interventions? Furthermore, we focus on the role that algorithmic tools, including machine vision, can play in such research efforts while being sensitive to their flaws and shortcomings. Which kinds of collaborations between humans and machines can we envision to better grasp and critically interrogate the dynamics of today’s digital visual culture? The different practices and formats discussed in this special issue (including data feminism, visual scores, machine vision, image networks, field guides) offer a range of approaches that seek to understand, reanimate, and change perspectives on our digital visual culture.
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This explanatory sequential mixed methods study explores the perceptions of academic and administrative managers responsible for teacher training at a public university in Colombia, as well as their views on improving such training after learning about the performance of teachers student teachers in the 2019 Saber Pro test, the differences in their test scores, and the relationships and statistical correlations between these outcomes and the students’ personal, family, socioeconomic and academic characteristics. Our findings show significant differences in the student teachers’ mean scores and performance when data are grouped according to personal, socioeconomic and academic conditions; a significant relationship between performance and student teacher characteristics; and correlations between critical reading scores and the other competencies assessed. Our data also highlight the lack of knowledge among academic and administrative managers about students’ life circumstances and the diversity of factors that may impact their performance; the importance of correlational data; the difference between expected and true outcomes; the inequity under which students seem to pursue their education; the limitations in access to resources; the training required for teachers to be able to analyze quantitative data and use specific software; the impact of teachers’ critical reading skills on student outcomes; the importance of data-driven decision-making; and the need for teachers to engage in quantitative research practices.
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