The multisemiotic dimension of 5G news: A corpus-based discursive news values analysis

Abstract

Chinese technology has emerged as a highly debated and newsworthy topic in recent years. While much scholarly attention has been devoted to analyzing news texts, the role of news photographs in shaping perceptions of newsworthiness remains underexplored. This study bridges this gap by examining the interplay between textual and visual news values in Chinese and US media coverage of 5G networks. Drawing on a corpus of 275 news articles published between 2017 and 2021 in China Daily, The Washington Post, and The New York Times, we employ the discursive news values analysis (DNVA) framework, augmented by corpus linguistic techniques and AI-driven image annotation tools. The findings reveal distinct patterns: Chinese media emphasizes Positivity, Personalization, and Proximity, whereas US media prioritizes Negativity, Eliteness, and Proximity. The differences in the multisemiotic construction of news values reflect underlying sociocultural ideologies and geopolitical dynamics, offering fresh insights into the media’s role in shaping global technological narratives.