Interactional and Interactive Metadiscourse in AI News Articles

AI technologies play a transformative role, making the clear communication of related advancements increasingly critical. Yet, the use of metadiscourse in technology news remains underexplored, particularly in how linguistic strategies are tailored to diverse audiences. This study investigates metadiscourse features in AI-related news articles, analyzing their interactive and interactional dimensions across headlines, subheadings, and body text. Using a corpus of 1,084 MIT News articles from 2015 to 2024, and applying Hyland’s metadiscourse framework, the study reveals distinct patterns across sections. Interactional features, such as hedges, boosters, and engagement markers, are most prevalent in the body, where they balance authority and audience connection, while the sub-header exhibits the highest relative density of such features. Interactive markers are most concentrated in sub-headers, with transitions dominating across all sections to aid coherence and reader orientation. Correlation analysis shows the strongest co-occurrence of both dimensions in the body, supporting complex argumentation, while headers and sub-headers emphasize clarity over the author’s stance. Temporal analysis indicates a marked decline in both metadiscourse dimensions during the 10-year period, reflecting a shift toward more neutral, concise, and standardized reporting shaped by digital reading habits and AI-assisted writing tools. These findings highlight the adaptive rhetorical strategies in AI journalism and demonstrate the importance of metadiscourse in framing information for effective public understanding.