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Artificial intelligence (AI) has emerged as one of the central topics of 2023 with extensive media coverage of the most relevant technologies and issues associated with this subject. In a highly competitive digital media landscape, search engine optimization (SEO) has become cybermedia’s primary strategy to increase visibility and attract more readers. The objective of this paper is to analyze the visibility of content published by the media relating to artificial intelligence, focusing on a selection of related keywords. The research also aims to investigate how this visibility has impacted both the technologies themselves and the analyzed media outlets. A total of 69 media outlets from 12 European Union countries, the United States, and the United Kingdom were examined. The results reveal a pronounced dominance of U.S. media, closely followed by Spanish media. There is an uneven distribution of media outlets across most of the countries analyzed, with two or three most of the of visibility. The search queries that contribute the most visibility to the analyzed media align with an informational intent, are of the long-tail type, and are associated with OpenAI technologies, particularly ChatGPT. Moreover, these queries are primarily found in news sections dedicated to science and technology. The findings underscore both the increasing interest in the subject and the effective SEO practices of certain media outlets.

SEO techniques are well-known in the academic field, but their evolution in online media for news production is still growing, especially in relation to AI and news monitoring. This study presents the results of an exploratory systematic review using the PRISMA-SCR framework, aiming to identify the evolution of SEO in journalism over the past five years, the ethical and information quality challenges associated with search engine optimization, and the interaction between SEO, AI, and news monitoring. The results indicate growing concern with how web visibility pursuit may override ethical journalism principles, reduce content diversity, and propagate misinformation, leading to “filter bubbles,” revealing a gap in this area. Given the scarcity of in-depth research, this study emphasizes the relevance of debating the close interrelation between SEO, AI, and news monitoring.

The main techniques and aspects to consider when starting to implement SEO strategies in libraries are presented. The process begins with an audit to assess the situation, and from there, it addresses the different elements to apply. It concludes by highlighting the importance of quality content, which should undergo continuous evaluation and review.

Introduction: SEO (search engine optimization) is the set of strategies that apply to content and websites so that they appear in relevant positions in search results. Given its importance in broad sectors of human activity, SEO has not gone unnoticed by academia, which has led to the development of different studies on this discipline. Objectives: under this premise, in this work, we aim to learn the academy's vision of SEO. In particular, we aim to explore the main characteristics of the corpus of published academic articles on SEO in the field of social sciences. The specific objectives are to determine key ideas, trends and key themes related to search engine positioning, including commonly used methodologies, as well as provide evidence-based input through a scoping review. Methodology: to carry out this research and determine what is the academia's vision about SEO, an exploratory systematic review has been applied, under a methodology known internationally as scoping review. For the development of the different phases of the systematized review, the SALSA framework has been followed, which has provided a basis of evidence from 56 documents. Results: the results of this research provide an overall characterization of academic studies in SEO from the social sciences and determine that they have focused, mainly, on knowing how general search engines like Google work, study SEO in relation to libraries and repositories, research positioning techniques in general and in particular business sectors, notably in journalism and the media, analyze the learning and training applied to search engine optimization and demonstrate the relationship between search engine positioning and user experience.

Introduction: SEO (search engine optimization) is the set of strategies that apply to content and websites so that they appear in relevant positions in search results. Given its importance in broad sectors of human activity, SEO has not gone unnoticed by academia, which has led to the development of different studies on this discipline. Objectives: under this premise, in this work, we aim to learn the academy's vision of SEO. In particular, we aim to explore the main characteristics of the corpus of published academic articles on SEO in the field of social sciences. The specific objectives are to determine key ideas, trends and key themes related to search engine positioning, including commonly used methodologies, as well as provide evidence-based input through a scoping review. Methodology: to carry out this research and determine what is the academia's vision about SEO, an exploratory systematic review has been applied, under a methodology known internationally as scoping review. For the development of the different phases of the systematized review, the SALSA framework has been followed, which has provided a basis of evidence from 56 documents. Results: the results of this research provide an overall characterization of academic studies in SEO from the social sciences and determine that they have focused, mainly, on knowing how general search engines like Google work, study SEO in relation to libraries and repositories, research positioning techniques in general and in particular business sectors, notably in journalism and the media, analyze the learning and training applied to search engine optimization and demonstrate the relationship between search engine positioning and user experience.

The main objective of this work is to carry out a comparative analysis between thirteen digital media websites that have won the Online Journalism Awards (ONA) and the World Digital Media Awards (WDMA) regarding the dimensions of interactivity, searchability and web visibility, through the application of an analysis protocol with nine parameters designed specifically for digital journalism (Santos-Hermosa et al. 2021; 2022). In this sense, it is an innovative methodological proposal applied to a real case study in digital communication. The results show different levels of achievement of the dimensions of interactivity, navigability and visibility in the awarded digital media; that allows establishing a ranking from highest to lowest score. Some outstanding trends are also identified with respect to each dimension of study. This shows a series of successful strategies and weaknesses linked to interactivity, searchability and web visibility. The application of the protocol turns out to be useful not only for researchers but also for digital journalism professionals, providing data for the creation of new services and products focused on the user experience.

The main objective of this work is to carry out a comparative analysis between thirteen digital media websites that have won the Online Journalism Awards (ONA) and the World Digital Media Awards (WDMA) regarding the dimensions of interactivity, searchability and web visibility, through the application of an analysis protocol with nine parameters designed specifically for digital journalism (Santos Hermosa et al. 2021;2022). In this sense, it is an innovative methodological proposal applied to a real case study in digital communication. The results show different levels of achievement of the dimensions of interactivity, navigability and visibility in the awarded digital media; that allows establishing a ranking from highest to lowest score. Some outstanding trends are also identified with respect to each dimension of study. This shows a series of successful strategies and weaknesses linked to interactivity, searchability and web visibility. The application of the protocol turns out to be useful not only for researchers but also for digital journalism professionals, providing data for the creation of new services and products focused on the user experience.

An exploration of how generative artificial intelligence (GAI) can assist in key tasks of the editorial processis presented. This includes operations such as peer review, identification of relevant content, detection of content generated by GAI (equated to plagiarism), and ultimately, the optimization of workflows. The described examples are practical instances that, for the time being, should be understood conceptually, as their practicality at any scale is not considered, depending on future developments in applications and their interconnectivity.

Artificial Intelligence (AI) is already integrated into news production strategies in some media outlets. Recently, generative AIs like ChatGPT and others have demonstrated their ability to enhance productivity in content production tasks, raising the question of how journalism faculties can address this new technology. This paper presents an academic study on the application of AI in higher communication studies. The study involved 4 in-depth interviews and 28 semi-structured interviews with university lecturers and researchers. The findings confirm varying degrees of convergence and divergence on different aspects of the technology, including the integration of AI in communication faculties, student training in AI usage, the introduction of AI and journalism as a subject area, and the potential uses of AI in news production and consumption. Additionally, this paper proposes a comprehensive training program on AI and journalism, focusing on its foundations, technical competencies, and ethical considerations.

Artificial intelligence (AI) is already integrated into news production strategies in some media outlets. Recently, generative AIs such as ChatGPT and others have demonstrated their ability to enhance productivity in content production tasks, raising the question of how journalism faculties can address this new technology. This paper presents an academic study on the application of AI in higher communication studies. The study involved 4 in-depth interviews and 28 semi-structured interviews with university lecturers and researchers. The findings confirm varying degrees of convergence and divergence on different aspects of the technology, including the integration of AI in communication faculties, student training in AI usage, the introduction of AI and journalism as a subject area, and the potential uses of AI in news production and consumption. Additionally, this paper proposes a comprehensive training program on AI and journalism, focusing on its foundations, technical competencies and ethical considerations.