Amal Htait

As the global population of older adults grows, AI-powered Voice Assistants (VAs) are explored as tools to mitigate loneliness, social isolation, and cognitive decline. By enabling intuitive, hands-free interaction, VAs provide a means to enhance independence, emotional well-being, and daily functioning for older adults. This paper presents a systematic review on older adults’ interactions with VAs, analysing 48 studies, which is more than double the scope of prior reviews. Studies were selected from an initial pool of 109 publications across three major Human-Computer Interaction (HCI) databases: Scopus, PubMed, and the ACM Digital Library. Through thematic analysis of research questions addressed in the selected studies, six key research themes were identified: (1) usage patterns and interaction behaviours, (2) adoption barriers and learnability challenges, (3) user experience and satisfaction, (4) cognitive and emotional impacts, (5) design considerations for older adults, and (6) future directions. A major finding is the VAs potential role in offering emotional companionship, particularly for socially isolated individuals. However, findings also suggested that technological illiteracy, trust concerns, and usability challenges hinder VAs’ adoption. This review highlights several important gaps in the existing literature. There is a lack of longitudinal research, and limited understanding of how these systems are used in real-world settings compared to controlled environments. Many studies also fail to report participants’ levels of technological experience and rely on samples that are not fully representative of the broader older adult population. Taken together, these limitations suggest that current research may not fully capture long-term use, contextual variability, or the diversity of older adults. In response, this paper outlines a set of evidence-based recommendations for future research and design. It emphasises the need to account for novelty effects in short-term studies and to adopt more ecologically valid approaches, such as in-home or longer-term deployments. It also highlights the importance of minimising artificial constraints that may influence user behaviour, and of systematically documenting user–device interactions alongside participants’ digital literacy. These steps can support more rigorous and representative evaluation practices, contributing to the development of voice assistant technologies that are better aligned with real-world use and more accessible, ethical, and effective for older adults.

Analyse de sentiment au service de la recherche de livres: Le Web est en croissance continue, et une quantité énorme de données est générée par les réseaux sociaux, permettant aux utilisateurs d'échanger une grande diversité d'informations. En outre, les textes au sein des réseaux sociaux sont souvent subjectifs. L'exploitation de cette subjectivité présente au sein des textes peut être un facteur important lors d'une recherche d'information. En particulier, cette thèse est réalisée pour répondre aux besoins de la plate-forme Books de Open Edition en matière d'amélioration de la recherche et la recommandation de livres, en plusieurs langues. La plateforme offre des informations générées par des utilisateurs, riches en sentiments. Par conséquent, l'analyse précédente, concernant l'exploitation de sentiment en recherche d'information, joue un rôle important dans cette thèse et peut servir l'objectif d'une amélioration de qualité de la recherche de livres en utilisant les informations générées par les utilisateurs. Par conséquent, nous avons choisi de suivre une voie principale dans cette thèse consistant à combiner les domaines analyse de sentiment (AS) et recherche d'information (RI), dans le but d'améliorer les suggestions de la recherche de livres. Nos objectifs peuvent être résumés en plusieurs points: • Une approche d'analyse de sentiment, facilement applicable sur différentes langues, peu coûteuse en temps et en données annotées. • De nouvelles approches pour l'amélioration de la qualité lors de la recherche de livres, basées sur l'utilisation de l'analyse de sentiment dans le filtrage, l'extraction et la classification des informations

Travel safety for women is a concern, particularly in India, where gender-based violence and harassment are significant issues. This study examines how the perception of safety influences women’s travel behaviour and assesses the potential of technology solutions to ensure their safety. Additionally, it explores how AI and machine learning techniques may be leveraged to enhance women’s travel safety. A comprehensive mobility survey was designed to uncover the complex relationship between travel behaviour, reasons for mode choice, built environment, feelings, future mobility, and technological solutions. The responses revealed that security and safety are the most critical factors affecting women’s travel mode choices, with 54% and 41%, respectively. Moreover, over 80% of women indicated a willingness to change their travel behaviour after experiencing fear, anxiety, or danger during their everyday journeys. Participants were 24% less willing to use ride-sharing services than ride-hailing services, which could affect the transition towards more sustainable transportation options. Furthermore, AI-based sentiment analysis revealed that 46% of the respondents exhibited signs of ‘anger’ regarding what could help women feel safer in transient environments. The practical implications of this study’s findings are discussed, highlighting the potential of AI to enhance travel safety and optimise future sustainable transport planning.

When pieces from an individual's personal information available online are connected over time and across multiple platforms, this more complete digital trace can give unintended insights into their life and opinions. In a data narrative interview study with 26 currently employed participants, we examined risks and harms to individuals and employers when others joined the dots between their online information. We discuss the themes of visibility and self-disclosure, unintentional information leakage and digital privacy literacies constructed from our analysis. We contribute insights not only into people's difficulties in recalling and conceptualising their digital traces but of subsequently envisioning how their online information may be combined, or (re)identified across their traces and address a current gap in research by showing that awareness is lacking around the potential for personal information to be correlated by and made coherent to/by others, posing risks to individuals, employers, and even the state. We touch on inequalities of privacy, freedom and legitimacy that exist for different groups with regard to what they make (or feel compelled to make) available online and we contribute to current methodological work on the use of sketching to support visual sense making in data narrative interviews. We conclude by discussing the need for interventions that support personal reflection on the potential visibility of combined digital traces to spotlight hidden vulnerabilities, and promote more proactive action about what is shared and not shared online.

Every day, people post information about themselves and others on online social networks, making such information accessible within their social circles but also, potentially, way beyond. While the information posted may seem benign or innocuous, small pieces of information, when tied together, can potentially reveal much more about the person than intended. Such cumulative revelations could expose them to risks such as identity theft, fraud or loss of employment. This paper describes findings from interviews about people's online interactions, focusing on their requirements and desires for improved ways to identify, understand and control cumulative revelations arising from their social media profiles that could put them at risk of grave consequences. These findings motivate our future work on how to better raise awareness among social media users of the risks and consequences to which combinations of posts may lead.