Simón Peña-Fernández

Nayla Escribano, Jon Ander González, Julen Orbegozo-Terradillos et al.

Parliamentary transcripts provide a valuable resource to understand the reality and know about the most important facts that occur over time in our societies. Furthermore, the political debates captured in these transcripts facilitate research on political discourse from a computational social science perspective. In this paper we release the first version of a newly compiled corpus from Basque parliamentary transcripts. The corpus is characterized by heavy Basque-Spanish code-switching, and represents an interesting resource to study political discourse in contrasting languages such as Basque and Spanish. We enrich the corpus with metadata related to relevant attributes of the speakers and speeches (language, gender, party...) and process the text to obtain named entities and lemmas. The obtained metadata is then used to perform a detailed corpus analysis which provides interesting insights about the language use of the Basque political representatives across time, parties and gender.

Simón Peña-Fernández, Ainara Larrondo-Ureta, Jordi Morales-i-Gras

Public digital conversation around major sporting events takes place within a hybrid system in which journalists and the media compete with new intermediaries, including influencers, to gain greater visibility and engage with audiences. This study analyses the Qatar 2022 World Cup as a case of high informational intensity and public opinion monitoring. To that end, social network analysis was applied to X/Twitter using the hashtag #Qatar2022, analysing 1,343 high-engagement accounts, including those of journalists, media and influencers, alongside a random sample of 5,000 users. The findings indicate that journalists are under-represented in the user population as a whole, but significantly over-represented among the highest-engagement accounts, and they maintain stable visibility. The media, by contrast, attract a lower average level of attention and tend to achieve only sporadic peaks of impact. Accordingly, journalistic authority on social media is observed less as dominance in terms of participation volume and more as the capacity to occupy reference positions when public attention is being shaped during the event.

Urko Peña-Alonso, Simón Peña-Fernández, Koldobika Meso-Ayerdi

This study examines journalists' perceptions of the impact of artificial intelligence (AI) on disinformation, a growing concern in journalism due to the rapid expansion of generative AI and its influence on news production and media organizations. Using a quantitative approach, a structured survey was administered to 504 journalists in the Basque Country, identified through official media directories and with the support of the Basque Association of Journalists. This survey, conducted online and via telephone between May and June 2024, included questions on sociodemographic and professional variables, as well as attitudes toward AI's impact on journalism. The results indicate that a large majority of journalists (89.88%) believe AI will considerably or significantly increase the risks of disinformation, and this perception is consistent across genders and media types, but more pronounced among those with greater professional experience. Statistical analyses reveal a significant association between years of experience and perceived risk, and between AI use and risk perception. The main risks identified are the difficulty in detecting false content and deepfakes, and the risk of obtaining inaccurate or erroneous data. Co-occurrence analysis shows that these risks are often perceived as interconnected. These findings highlight the complex and multifaceted concerns of journalists regarding AI's role in the information ecosystem.