采用来自微博问答二手数据分析与随机对照实验的混合研究方法，探索在线付费问答情境中，问题文本的语言特征对用户付费围观答案的影响，及其关系背后的内在心理机制。研究发现：问题描述的可读性和情绪消极性均对答案围观收益具有显著正向影响；问题描述的详尽性与答案围观收益间存在倒U形关系；问题描述的详尽性对可读性（情绪消极性）与答案围观收益间的关系具有二次调节作用；用户感知到的加工流畅度、情绪感染和信息丰富度在问题文本特征与用户付费围观答案关系之间发挥中介作用。

Employing a mixed-methods approach, including secondary data analysis and randomized controlled experiments, we explore the impact of linguistic characteristics of question descriptions on content monetization and their underlying mechanisms. The results reveal that: question readability and emotional negativity have positive effects on the answer revenue; there is an inverted U-shaped relationship between question elaborateness and answer revenue; question elaborateness moderates the relationship between readability (and emotional negativity) and answer revenue; and perceived processing fluency, emotional contagion, and information richness mediate the effect of question linguistic characteristics on users’ willingness to pay to view the answer. This research provides valuable insights and recommendations from the perspectives of semantic analysis and user psychology for optimizing digital content production and enhancing the digital content ecosystem.