Disrupting or Conforming: A Computational Analysis of International News Coverage of Africa on YouTube - Madrid-Morales, Dani (AoIR Selected Papers of Internet Research, 2026)
International news organizations have historically reinforced narratives of poverty, conflict, and crisis in their portrayal of Africa, often aligning with broader geopolitical power structures. While recent years have seen the rise of new broadcasters such as Al Jazeera, CGTN, and TRT World, it remains contested whether they challenge or reproduce dominant Anglo-American media framings. The emergence of digital platforms, particularly YouTube, has further complicated these dynamics, enabling both alternative storytelling and the persistence of existing hierarchies.This study examines whether news coverage of Africa on YouTube by international organizations diverges from legacy media portrayals, whether new actors disrupt established narratives, and how audiences engage with these representations. A dataset of approximately 250,000 videos from twelve major international broadcasters is analyzed using BERTopic, a machine-learning-based topic modeling technique, to identify dominant themes and frames in news coverage. Audience engagement is examined through sentiment analysis and discursive clustering of YouTube comments, offering insights into whether users challenge or reinforce dominant narratives.By critically examining the intersection of international journalism, digital platforms, and audience agency, this paper contributes to ongoing debates about the role of online media in shaping global news flows. It interrogates whether YouTube facilitates a rupture in traditional representations of Africa or whether it ultimately serves as a new distribution channel for entrenched media narratives. As global media consumption increasingly shifts to digital platforms, understanding how Africa is framed in these spaces and how audiences respond is crucial for broader discussions on media influence, representation, and power.