Analysis of scientific research on the opposing models of paywalls and clickbait in online media and their relationship with artificial intelligence - Monsalve-Alama, Antonio; Marti-Sanchez, Myriam; Berné-Martínez, José-Miguel (Transformations In Business & Economics, 2026)
This study examines scientific research on paywalls and clickbait as contrasting revenue models in online media and explores how artificial intelligence (AI) is disrupting these models and journalism more broadly. It evaluates the scope of academic interest in these topics and identifies gaps in current scholarship. Using bibliometric analysis of Web of Science (WoS) Core Collection data and science-mapping techniques in VOSviewer, the study analyses publication trends, influential authors, and thematic clusters from the early 2010s to 2024. Findings show that although clickbait receives more scholarly attention, paywall research achieves greater impact, reflecting its focus on revenue strategies, consumer behaviour, and willingness to pay. The prominence of clickbait studies relates to concerns about engagement, credibility, and misinformation. Another key finding is that, while AI is transforming journalistic production, personalisation, and automation, its integration into media business models remains limited. The study underscores the need for interdisciplinary approaches to support sustainable digital media ecosystems.
Keywords: media business models; paywall; clickbait; AI; bibliometric analysis