Reshaping Digital Social Reality in the AI Era: A Data-Driven Analysis of University Students’ Exposure to Digital Harassment in Emerging Countries

Digital harassment is an increasing challenge in higher education, with implications for students’ psychological well-being, perceived safety, and engagement in digital learning. As artificial intelligence (AI) increasingly mediates communication, visibility, and interaction across educational platforms, students’ exposure to online harm is shaped not only by individual behaviour but also by algorithmically structured interaction environments. Understanding these conditions is essential for protecting student well-being and supporting sustainable participation in AI-enhanced learning. This study examines university students’ exposure to digital harassment in AI-mediated learning environments using an expanded Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Survey data were collected from 2185 students, including Saudi nationals and international students enrolled in Saudi Arabian universities, representing Saudi Arabia and 32 other developing and emerging countries (33 countries in total). The model analyses associations among technological literacy, cybersecurity awareness, social media engagement intensity, digital identity visibility, AI-mediated interactions, and cultural norms, while also accounting for disciplinary and cultural context differences. The results indicate that AI-mediated interactions are most strongly associated with exposure to digital harassment. Higher social media engagement, more restrictive cultural norms, and greater visibility of digital identity are associated with increased exposure, whereas technological literacy and cybersecurity awareness are associated with lower reported exposure. Furthermore, greater exposure to digital harassment is linked to poorer mental health outcomes and reduced continuity in e-learning participation. Overall, the findings suggest that digital harassment in AI-driven educational settings is a structural sociotechnical issue associated with greater embeddedness in algorithmically mediated learning environments, rather than an isolated behavioural issue. The study highlights the need for responsible AI governance, enhanced digital literacy education, and culturally responsive institutional policies to support inclusive and sustainable higher education.