Purpose: The role of government in the global digital transformation is to ensure that digital infrastructure is reliable and efficient enough to guarantee an entrepreneurial ecosystem for investment in innovation and startups. This paper presents a case study showing how local policies have been used to create an effective startup ecosystem in Barcelona. This paper aims to provide a detailed analysis of the key elements of the startup ecosystem, including the role of local government. Design/methodology/approach: This study uses an exploratory case research approach and proposes a theoretical framework to study the Barcelona innovation ecosystem, drawing on interviews, research observations and an analysis of the literature. Findings: By applying its conceptual framework tools, the research is able to identify the key elements making up the startup ecosystem and classify the impact of digital transformation policies into three stages: creating the ecosystem, fostering feedback within the ecosystem by encouraging the first generation of entrepreneurs to interact with the second and third and attracting foreign capital and talent to this innovation ecosystem. Originality/value: The novelty of this work lies in its time frame and geographical scope, as it provides an analysis of the digital transformation policies in Barcelona’s local startup ecosystem over a 30-year period. This research offers deeper insight into the role of public policies in the startup ecosystem in Barcelona, as well as the impact of digital transformation policies on startup ecosystems in general.

Comments and information appearing on the internet and on different social media sway opinion concerning potential remedies for diagnosing and curing diseases. In many cases, this has an impact on citizens’ health and affects medical professionals, who find themselves having to defend their diagnoses as well as the treatments they propose against ill-informed patients. The propagation of these opinions follows the same pattern as the dissemination of fake news about other important topics, such as the environment, via social media networks, which we use as a testing ground for checking our procedure. In this article, we present an algorithm to analyse the behaviour of users of Twitter, the most important social network with respect to this issue, as well as a dynamic knowledge graph construction method based on information gathered from Twitter and other open data sources such as web pages. To show our methodology, we present a concrete example of how the associated graph structure of the tweets related to World Environment Day 2019 is used to develop a heuristic analysis of the validity of the information. The proposed analytical scheme is based on the interaction between the computer tool—a database implemented with Neo4j—and the analyst, who must ask the right questions to the tool, allowing to follow the line of any doubtful data. We also show how this method can be used. We also present some methodological guidelines on how our system could allow, in the future, an automation of the procedures for the construction of an autonomous algorithm for the detection of false news on the internet related to health.

In this paper, we describe a new trend analysis and forecasting method (Deflexor), which is intended to help inform decisions in almost any field of human social activity, including, for example, business, art and design. As a result of the combination of conceptual analysis, fuzzy mathematics and some new reinforcing learning methods, we propose an automatic procedure based on Big Data that provides an assessment of the evolution of design trends. The resulting tool can be used to study general trends in any field—depending on the data sets used—while allowing the evaluation of the future acceptance of a particular design product, becoming in this way, a new instrument for Open Innovation. The mathematical characterization of what is a semantic projection, together with the use of the theory of Lipschitz functions in metric spaces, provides a broad-spectrum predictive tool. Although the results depend on the data sets used, the periods of updating and the sources of general information, our model allows for the creation of specific tools for trend analysis in particular fields that are adaptable to different environments.

Medición de la influencia de usuarios en redes sociales: propuesta SocialEngagement

This study analyses future trends in lifelong learning in the Peruvian context. Using the DeflyCompass model, an artificial intelligence tool, the main trends affecting the evolution of postgraduate studies were identified, including the impact of generative AI on the personalisation of education, the transformation of work and the growth of Generation Z as key players in the educational environment. The methodology applied combines a mixed qualitative and quantitative approach, based on the opinion of experts—45 participants from seven public/private universities in Peru—the technique of semantic projections, the use of generalist search engines and specialised databases, and other digital management resources such as Google Scholar profile analysis and online marketing campaign design tools. In particular, a total of 150 scientific papers and 300 articles from generalist sources were analysed. This approach made it possible to select, analyse and quantify the main trends in higher education in Peru and to assess their potential impact on the future development of graduate schools, specifically in the case of the Pontificia Universidad Católica de Perú (PUCP). The results highlight the importance of adapting postgraduate studies to new demands, such as the adoption of generative AI, the adaptation of personalised education and the integration of digital technologies to enhance the personal and professional growth of students. It also highlights the need to incorporate strategies that address the transformation of work, with a focus on developing digital skills and preparing for an ever-changing work environment. The study thus provides a guide for Peruvian universities on how to adapt their graduate programmes to emerging trends, promoting a flexible and technologically advanced education that responds to the needs of future professionals.

Esta investigación presenta un modelo de análisis diseñado para detectar, organizar y clasificar la singularidad en la educación superior basado en estudios de futurización. Para ello, se recopilan evidencias con el fin de identificar rasgos diferenciales en el campo educativo, lo que permite a las universidades tomar decisiones estratégicas en entornos complejos. El estudio se fundamenta en técnicas de análisis respaldadas por investigaciones futurísticas para identificar tendencias y organizaciones innovadoras en diversos contextos educativos. Estas singularidades se clasifican y organizan mediante una propuesta metodológica mixta que combina investigación confirmatoria y la recopilación de datos cualitativos y cuantitativos. Los resultados del estudio proporcionan una visión de 55 organizaciones de educación superior con características singulares, destacando aspectos importantes de cada una de ellas. Además, se valida la utilidad del instrumento desarrollado como una herramienta crucial que permite a las universidades revisar y adaptar constantemente sus prácticas educativas, manteniéndolas actualizadas y respondiendo a los avances sociales y tecnológicos en un mundo en constante cambio. Asimismo, la investigación busca fomentar un debate sobre el papel futuro de las universidades como actores en una sociedad dinámica, compleja e incierta. Esto resalta la importancia de que las universidades estén preparadas para enfrentar los desafíos y aprovechar las oportunidades que surgen en este contexto cambiante.