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.

翻译：疑问句在新闻语篇中的使用已在语言学和会话分析领域得到研究，但主要集中于广播访谈及相对较小（通常为英语）的语料库，而大规模新闻计算研究很少区分疑问句与陈述句或辨析其功能差异。本文通过混合方法研究当代法语数字新闻中的"提问政治学"，将上述不同研究脉络相结合。基于2023年1月至2024年6月间发布的逾百万篇新闻文章，我们自动检测疑问立场、估测其功能类型并定位文本中的答案（若存在），将这些量化指标与基于疑问句语义及语用理论进行定性标注的子语料库相联结。疑问句虽稀疏分布但呈现系统模式：它们主要承担议题引入或组织功能，其余多数案例为信息寻求或回声类疑问句，而显性引导问句或附加问句较为罕见。尽管疑问句密度和类型组合因媒体渠道和话题而异，我们的启发式分析表明，疑问句绝大多数在文章内部得到承接，且通常与后续类似答案的文本跨度相关联——这种关联更多通过记者的叙事声音实现，较少通过引述话语呈现。疑问语境中密集出现具名个体、组织机构及地理名称，而公众与广泛社会群体被提及的频率则显著较低，这表明疑问语篇倾向于凸显已具影响力的行动者与场域，从而展现出强烈的个人化特征。我们展示了如何在大规模语料层面将疑问立场、文本承接与叙事声音进行操作化，并论证计算方法与语用学、社会学视角的结合有助于阐释提问实践如何形塑当代新闻语篇。