Artificial intelligence (AI) has been progressively expanding over the last decade, with its transversal application to the journalistic process and the engaging of media and technology companies in developing specific tools and services. This research offers a first catalogue of Spanish technological companies and institutions that develop AI systems applicable to journalism, with services and features grouped into three phases of the journalistic process: 1. Automated gathering and documentation of information; 2. Automated production of content; and 3. Information distribution and audience relations. The research uses a methodology of in-depth interviews with 45 innovation heads of Spanish-based companies and technological centres specialised in the development of AI (N = 25), and is supported by questionnaires to systematise four study categories: company profiles, tools, journalism-specific services and future trends. The results confirm a clear evolution of Spanish technological companies within the AI sector, with services and tools available for the whole journalistic process, mainly in the information gathering and content distribution phases related to monetisation; the automated news production phase is thereby overshadowed. The offering is diversified in terms of formats -textual, audiovisual, sound- and platforms, especially web and social media. The companies consulted testify to the profitability of its implementation and note a growing interest from the media, but warn of an uneven progress that reflects “slowness”, “distrust” and “lack of knowledge” regarding the application of AI.

La relevancia de las redes sociales como agentes fijadores de la agenda y de los prosumidores como creadores y consumidores de contenido al margen de los medios incentivan una comunicación política centrada en el uso de plataformas digitales como parte de su estrategia persuasiva directa hacia el usuario-votante. Esta investigación analiza la agenda temática y el discurso político en Twitter como espacio de microsegmentación para ahondar en la estrategia de personalización, polarización y discurso emocional de los candidatos políticos en periodo electoral. Para comprobar este proceso de desintermediación comunicativa, se realiza un estudio de caso centrado en los seis candidatos principales a las elecciones de la Comunidad de Madrid durante la campaña electoral (abril-mayo, 2021). La metodología combina un análisis de contenido y del discurso en torno a los tweets emitidos por los representantes políticos en su perfil de Twitter durante este periodo (N=817), así como los vídeos (N=637) e imágenes (N=202) que los acompañan. La codificación se realiza mediante un software propio que permite descargar los tweets, obtener las interacciones y clasificar los mensajes en torno a cuatro categorías: fuente del tweet; temática, diferenciando entre asuntos políticos y preocupaciones ciudadanas según el CIS (2021); encuadre o framing; y elementos de narrativa multimedia. Los resultados principales confirman que en la comunicación política desintermediada en redes sociales, los líderes políticos emplean un discurso personalista, polarizado y emocional, con alto engagement en torno a la narrativa multimedia. La investigación constata un discurso electoral que versa sobre política, pero no de políticas.

The expansion of the use of artificial intelligence (AI) across different stages of production and distribution in journalism is opening a debate on its applications within newsrooms and in business models. This research studies how different media outlets, media groups and institutions are beginning to create internal regulations for the use of AI, both from a technical and an ethical perspective. To do so, an international sample (N = 45) of editorial stylebooks and internal self-regulatory guidelines published between 2023 and early 2025 have been compiled—all links are openly available here—and put through a process of content analysis. The results indicate that the self-regulatory guidelines emerge from an individual initiative of the media themselves, with a focus on limiting the use of generative AI, particularly in text creation. The guidelines emphasize ethical commitments such as transparency, content verification, and respect for data and copyright while underlining the importance of human oversight. Key objectives include avoiding bias, ensuring information quality, and strengthening audience trust. Despite progress, regulation remains in its early stages and requires continuous adaptation to keep pace with technological advancements.

Digital transformations entail continually reviewing the various Communication models and processes. The influence of the media themselves as agenda setters for an ever more active audience and social networks that select and make certain content they receive viral are also affected by such a convergent context. This current research analyses a model called here the ‘triple agenda’ within the media themselves, in which the journalistic criterion of relevance and their audience’s preferences in the web and the networks travel along different paths. The proposal includes the users and the viral effect as influencing agents in the shape and selection of news, generating a news gap of interests between the media and their audiences. In order to test this model, we study an exploratory case in ElPaís.es, applying a content analysis to the information (n=420) distributed among the online front page, what is most read by the audience in its webpage, and the most viral in its Twitter account. The main objective is to check whether or not these three spheres of relevance operate independently, showing different informative interests f rom the thematic selection that the medium establishes f rom its agenda, its audience and its social networks. The results confirm that there is a gap in the informative interests of the three spheres analysed, especially between the agenda marked by the medium and the interests that are reflected in their web audience, which is more attracted to soft news and the clickbait technique; while there is a greater coincidence of interests between the newspaper’s front page and the users’ selection in their social networks.

The communicative effects of disintermediation caused by social media promote the expansion of personalist and emotional political discourses that reach the audience directly and evade the traditional journalistic filter. This phenomenon leads to new political communication tactics, but also exposes citizens to potentially fraudulent, contaminated or polarised content. In this context, framed in post-truth, the term ‘fake news’ gains relevance as a way of referring to disinformation and as a political and performative argument that can be weaponised. This research aims to analyse such use in the discourse of the former president Donald Trump during his presidential term (2017-2021), focussing on Twitter as the main platform in his political communication strategy online. To analyse this, we resort to a methodological triangulation of content, discourse, and sentiment analysis, with the latter combining both lexicon and artificial intelligence (AI) techniques through machine learning on the basis of deep learning and natural language processing, which is applied to his messages published with the term ‘fake news’ (N = 768). The analysis of the sample, provided here in an open dataset, employs self-developed software that allows each unit of analysis to be filtered and coded around its predominant themes, sentiments, and words. The main results confirm that Trump’s attribution of ‘fake news’ focusses on three main topics: the media (53%), politics (40%) and his cabinet (33%). It also shows how the former president resorts to a personalist agenda, focussed on the defence of his proposals and his team (80%) by delegitimizing his opponents and the press, with a negative tone (72%) loaded with derogatory terms, confirming a weaponised strategy of the term ‘fake news’ as a political argument of disinformation and disintermediation.

The competition to attract audiences has led to an increase in sensational or misleading headlines and content, with the aim of garnering user clicks in the news media. This dynamic alters the journalistic manner in which news is presented, and it does so by reducing informative quality and eroding the trust of the audience. This study examines the proliferation of clickbait strategies on the front pages of reputable international ‘serious’ press and how it manifests in readers’ consumption and sharing habits. We carried out a comparative content analysis of digital news articles from four international media sources (N = 1680): The Guardian (UK), The New York Times (USA), El País (Spain) and Público (Portugal). Our results confirm the existence of clickbait (N = 516) on the front pages, the most read content and the articles most shared on social media. Most clickbait titles resort to headline strategies of containing incomplete information that affect both hard and soft news topics. This particular finding highlights the inclusion of clickbait in the agenda of ‘serious’ journalism, despite the negative implications on information quality and trust. Associated with irrelevant content, this ‘hook’ captures the attention of the online audience more than the social media audience.