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.