Abstract
In this study, we compared different survival models using machine learning (ML) techniques to assess the impact of enriching survival models with features extracted from topological data analysis (TDA). Using a clinical dataset on lung transplantation, we compared the Cox model, random survival forests (RSF), and the DeepSurv deep neural network, along with their TDA-enriched versions. TDA uses persistent homology and generates descriptors that capture the global and multiscale structures present in the data that do not appear in Euclidean spaces. The results show that integrating these descriptors improves predictive performance, increasing the C-index and enhancing risk discrimination. Thus, the integration of TDA and ML emerges as a promising alternative for modeling survival in complex biomedical data. © IFIP International Federation for Information Processing 2027.

Abstract
Digital platforms transform children’s relationships with media through algorithmic marketing strategies targeting Generation Alpha. This ethnographic study explores how digital platforms shape children’s musical cultures through algorithmic recommendation systems and commercial content strategies. Focusing on 22 children aged 8–11 in northern Portugal, drawing-talks and participant observation reveal the emergence of musicmedia, a hybrid convergence of music, visuals, platforms, and social practices, amid tensions between algorithmic prescription and children’s creative agency. Key findings demonstrate TikTok as primary discovery engine, funneling children through personalized recommendation sequences toward sustained YouTube and Spotify engagement. Children actively curate playlists, optimize content trajectories, and reappropriate viral fame narratives, transforming platform logics into spaces for identity experimentation and peer validation. Algorithms serve dual functions: prescriptive content delivery optimizing engagement conversion and aspirational narratives fostering long-term retention. Theoretically, results advance understanding of musicmedia as sociocultural phenomenon negotiating children’s imaginative resistance against platform architectures. Findings challenge protectionist approaches, highlighting sophisticated digital competencies among Generation Alpha. Implications inform music marketing strategies leveraging virality-sequencing, authentic aspiration amplification, and algorithmic transparency within children’s digital ecosystems.

Abstract
Marketing communication has changed a lot in recent decades, mainly due to new technologies and shifts in how consumers behave. Generation Alpha, born from 2010 onwards, is the first to grow up fully surrounded by digital media, but traditional advertising is still part of their everyday lives. This makes it important to understand how they see and react to both online and offline marketing. This study looks at Generation Alpha’s attitudes toward marketing communication, focusing on how they perceive, prefer, and respond to different advertising formats. It uses a qualitative approach with focus groups involving children aged 6 to 13, allowing a closer look at their experiences and emotional reactions to ads on digital platforms, social media, television, and outdoor media. The results show a clear preference for digital communication, especially formats that are interactive, audiovisual, and entertaining. Online advertising tends to be viewed as more appealing and relevant when it includes storytelling, strong visual elements, and chances to interact. Even so, offline advertising still plays a role, particularly in family contexts, where exposure often happens with parents or in shared viewing moments. In both online and offline environments, aspects such as transparency, credibility, and the perceived honesty of the message are central to whether advertising is accepted or rejected. Overall, the study helps clarify how younger consumers relate to marketing communication and points to practical paths for brands that want to build strategies that are ethical, credible, and effective for a digital-native generation.

Abstract
The rapid evolution of artificial intelligence (AI) has transformed customer service environments, with chatbots emerging as key tools for improving efficiency, responsiveness and personalization. Despite their growing adoption across sectors such as retail, finance, healthcare and education, uncertainty persists regarding how users perceive these systems and which factors shape their satisfaction. Existing research points to clear advantages of chatbots but also highlights limitations related to trust, empathy and the handling of complex interactions.? This paper examines how AI-based chatbots influence user satisfaction in customer service contexts and identifies the interactional factors that most strongly shape users’ evaluations. A quantitative, cross-sectional survey was conducted using a questionnaire that explored perceived interaction quality, trust in AI systems, social presence, usefulness, responsiveness and limitations experienced during automated service. Statistical analysis was used to identify relationships between chatbot use, user satisfaction and the variables contributing most strongly to positive or negative evaluations.? The results show that although most respondents had previous experience with chatbots, their assessments varied across performance dimensions. Ease of use received the most favourable ratings, while problem resolution showed the greatest variability, suggesting that chatbots remain more effective for simple requests than for complex issues. Trust and clarity of information were generally positive but displayed substantial dispersion, reflecting heterogeneous user experiences. More than half of users required human assistance after chatbot interaction, and barriers such as lack of need, privacy concerns and perceived inconsistencies were frequently reported. Despite these challenges, overall satisfaction and recommendation levels were positive, indicating that effectiveness in resolving issues is central to user acceptance.

Abstract
The digital transition has transformed the organisational and creative dynamics of communication agencies, generating new market demands and redefining the role of creative professionals. This study investigates how agency creatives perceive the impact of digital platforms and the internet on professional practices, creative autonomy and strategic decision-making. Adopting a qualitative approach, semi-structured interviews were conducted with seven experienced professionals working in Portuguese communication agencies. The corpus was analysed using the Iramuteq software, which enabled Descending Hierarchical Classification, Correspondence Factor Analysis, similitude mapping and word cloud visualisation. Results reveal that digitalisation is not perceived merely as a technological update, but as a structural force that intensifies production cycles, imposes data-driven evaluation and reshapes the symbolic value of creativity. Although digital tools expand expressive possibilities, they simultaneously restrict time for conceptual exploration and increase performance pressures. The findings demonstrate that contemporary creativity has become a negotiation between artistic intention and measurable market outcomes. The study concludes that sustaining creative autonomy requires organisational reform, interdisciplinary learning and strategic anticipation of digital trends. Insights highlight the need for agency models that protect creativity while embracing technological innovation.

Abstract
This study examines how leading skatewear brands construct symbolic meaning and digital identity on Instagram by analyzing content typologies, message structures, textual features and engagement patterns. A quantitative content analysis was conducted on one hundred and twenty posts from six major brands (Vans, Nike SB, Stussy, Element, Dickies and Carhartt WIP), selected according to digital relevance and recency. Data collection included interaction metrics, publication formats, caption use and specific textual elements, enabling the identification of systematic visual and textual communication patterns. A structured coding grid was applied to classify all variables under analysis. The study contributes to understanding the processes through which brands translate cultural values into symbolic digital narratives, demonstrating how Instagram operates as a primary environment for meaning making, identity signaling and community formation within the urban fashion ecosystem. Results confirm the centrality of visual composition, cultural references and textual economy in shaping symbolic coherence and perceived authenticity. Two dominant communicational profiles emerge: cultural and aspirational brands that rely on emotionally driven narratives associated with art, music and public figures, and pragmatic or institutional brands that adopt functional and objective messaging. Variations in the use of emojis, hashtags and captions indicate differentiated strategies for visibility enhancement and audience engagement. Overall, the findings advance the literature on digital branding, symbolic identity construction and communicational meaning making within social media environments applied to skatewear brands.