Politics of Questions in News: A Mixed-Methods Study of Interrogative Stances as Markers of Voice and Power

2026-03-23

AI Summary

This study addresses a gap in the computational analysis of interrogatives in news discourse, particularly the lack of large-scale investigations integrating pragmatic and sociological perspectives on their role as markers of discursive power and narrative voice. Drawing on a corpus of over one million French-language digital news articles published between January 2023 and June 2024, the project operationalizes the constructs of “interrogative stance,” “textual uptake,” and “narrative voice” through a hybrid methodology combining natural language processing with manual pragmatic annotation to automatically classify interrogative types and locate corresponding answers. Findings reveal that, despite their relatively low frequency, interrogatives exhibit systematic patterns—primarily serving agenda-setting or information-seeking functions—and are frequently answered by journalists adopting a narrative voice, with pronounced focus on specific individuals and institutions, thereby exposing the political and personalized dimensions of questioning in journalistic discourse.

Technology Category

• Natural Language Processing: Discourse, Pragmatics & Argument Mining
• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Intelligent Query Processing

Application Category

• Web Mining and Content Analysis: Community question answering
• Social Networks and Social Media: Social media analysis through the lenses of networks
• Search and Retrieval-Augmented AI: Agentic search

Abstract

Interrogatives in news discourse have been examined in linguistics and conversation analysis, but mostly in broadcast interviews and relatively small, often English-language corpora, while large-scale computational studies of news rarely distinguish interrogatives from declaratives or differentiate their functions. This paper brings these strands together through a mixed-methods study of the "Politics of Questions" in contemporary French-language digital news. Using over one million articles published between January 2023 and June 2024, we automatically detect interrogative stances, approximate their functional types, and locate textual answers when present, linking these quantitative measures to a qualitatively annotated subcorpus grounded in semantic and pragmatic theories of questions. Interrogatives are sparse but systematically patterned: they mainly introduce or organize issues, with most remaining cases being information-seeking or echo-like, while explicitly leading or tag questions are rare. Although their density and mix vary across outlets and topics, our heuristic suggests that questions are overwhelmingly taken up within the same article and usually linked to a subsequent answer-like span, most often in the journalist's narrative voice and less often through quoted speech. Interrogative contexts are densely populated with named individuals, organizations, and places, whereas publics and broad social groups are mentioned much less frequently, suggesting that interrogative discourse tends to foreground already prominent actors and places and thus exhibits strong personalization. We show how interrogative stance, textual uptake, and voice can be operationalized at corpus scale, and argue that combining computational methods with pragmatic and sociological perspectives can help account for how questioning practices structure contemporary news discourse.

Problem

• interrogatives
• news discourse
• voice
• power
• questioning practices

Innovation

• interrogative stance
• mixed-methods corpus analysis
• computational pragmatics
• voice and power in news
• question-answer patterns