This study investigates the attitudes of young individuals aged 15–35 years toward digital communication, with a focus on digital skills, citizenship, and civic engagement. Utilising data from the European Social Survey (ESS) round 10 (2020), the research explores variations across over 30 European countries, examining responses to the ESS’s rotating module on “Digital social contacts in work and family life.” Key questions, such as exposure to misinformation and online political engagement, are analysed to uncover factors influencing young Europeans’ perceptions of information and communication technology (ICT). The study explores digital scepticism, optimism, and digital skills, linking them to civic participation and socio-demographic factors. Statistical analysis, including chi-square tests and multiple regression analysis, identifies predictors and disparities among countries. Correspondence analysis dissects interrelationships among categories, constructing plots to showcase proximity between factors. Evaluating Internet accessibility, civic engagement, and connectivity issues, the study also compares data with the prior ESS round (round 9, 2018) to assess changes over the past 4 years. Through empirical investigation, this study sheds light on young Europeans’ perspectives on ICT, offering valuable insights into the complex interplay between digital communication, civic engagement, and beneficial Internet time.

Digital technologies play an increasingly significant role in the everyday lives and culture of children and young people, but research and societal discussions often focus solely on the perceived risks and concerns associated with their use. This narrow focus does not recognise children’s agency in digital spaces. In this chapter, we address this gap by exploring the meaning children and young people attribute to their leisure-time use of digital technology, from their own perspective. Our study draws on interviews and digital diary data collected in Austria, Greece, Norway, Romania, and the United Kingdom. The findings highlight that children not only perceive digital technologies as a source of entertainment but also as a meaningful part of their leisure activities, enabling communication, socialisation, play, and learning. However, there appears to be a generational gap in the meaning attributed to leisure-time activities, as there is a discrepancy between children’s and parents’ perspectives. Consequently, parents impose restrictions on content and screen time, thereby limiting children’s agency to some extent. Nevertheless, children’s negotiations regarding screen time, content choices, and decisions about whom and what to engage with can be seen as their attempts to expand and assert their agency.

This chapter explores young people’s political participation on and with social media from an ecosystemic perspective. Drawing from an analysis of interviews, ethnographic social media observations, and digital storytelling workshops conducted in Estonia, Greece, and the United Kingdom, we highlight the entanglement of young people’s participatory repertoires with social media, but also with their leisure and school lives and family relationships. We explore how young people invested in issues of racial justice, gender and LGBTQ justice, and climate justice, incorporate or push back against digital technologies, and how that is mediated by their perceptions of social media affordances, imaginary audiences, their sense of self-efficacy, political agency, and digital literacies. The findings shed light on the complex interplay between personal, structural, and environmental factors that shape young people’s political participation, and highlight the situational nature of how activism and politics are defined and the role that social media is attributed within both.

The interplay between technology and societal norms often reveals a troubling reality: machine learning systems not only reflect existing gender stereotypes but can also amplify and entrench them, making these biases harder to detect and address. This paper adopts an interdisciplinary approach, combining quantitative and qualitative methods with recent technological advancements, such as machine learning techniques for textual analysis and computational linguistics, to offer a new framework for understanding occupational gender bias in machine learning. The study is motivated by persistent gender inequalities in the labour market and rising concerns about gendered algorithmic bias, as outlined in the European Commission’s Gender Equality Strategy 2020–2025. Focusing on language translation technologies, the research explores how machine learning may perpetuate or amplify gender stereotypes, aiming to foster more inclusive digital systems aligned with EU strategic goals. More specifically, it investigates occupational gender segregation and its manifestations in various forms of gender bias in machine learning across English, French, and Greek. The study introduces a classification of gender biases in machine learning, providing insights into professional areas needing intervention to address gender imbalances and identifying enduring stereotypical representations in textual data. To support this, statistical analysis is conducted to explore gender variations in occupations over the past thirteen years, using official data and international classifications such as the International Standard Classification of Occupations (ISCO-08). Moreover, gendered occupational distributions are extracted from 200,920 text instances in the three languages, revealing significant discrepancies between official labour statistics and the training data.

In this chapter, I reflect upon the theoretical and political implications of the so-called ‘refugee crisis’ both in terms of governance and sovereignty. The analysis that follows is based on empirical material, namely in-depth semi-structured interviews with different relevant stakeholders, i.e. representatives of authorities, such as the former Ministry of Migration Policy and the Asylum Service, representatives of EU agencies, such as Frontex and DG ECHO, as well as volunteers and activists from Greece and other countries, like Turkey, Spain and the United States of America. I focus on pre-existing and emerging internal contradictions between different actors who have been dealing with refugees. In other words, I try to capture the contingent character of new geographies of control that occurred with the establishment of the ‘hotspot approach,’ in correlation with the shifts in state sovereignty as it has been repositioned through the active involvement of non-state actors – from non-governmental organisations to international organisations and EU agencies – in the refugee/migration management.

This chapter offers an exploration of the methodological potentials, challenges, and pitfalls associated with conducting multimodal research on patterns of digital socialisation during leisure, while focusing on the involvement of children as co-researchers. A comprehensive research design is suggested for investigating children and young people’s digital leisure activities using a multimodal approach. This design aims to explore communication and representations by leveraging an innovative process of integrating and interpreting information from diverse modalities. This process, known as semantic data integration, allows for a cohesive analysis of multimodal data, enabling a deeper understanding of the subject matter. The design emphasises the active involvement of research contributors, who not only participate as subjects but also play a role as co-researchers. The chapter provides a detailed description and critical assessment of the methodologies adopted across all parts of the fieldwork conducted to investigate children’s online leisure habits and digital technologies use and identifies the significant qualities of a multimodal and multi-method approach. The methods are evaluated to deliver suggestions for practises that can be adopted in having children play an active part through research implementation. Semantic integration is suggested to bridge the gap between different modalities and extract comprehensive understanding of collected data.