Discussing research-sensemaking questions on Community Question and Answering (CQA) platforms has been an increasingly common practice for the public to participate in science communication. Nonetheless, how users strategically craft research-sensemaking questions to engage public participation and facilitate knowledge construction is a significant yet less understood problem. To fill this gap, we collected 837 science-related questions and 157,684 answers from Zhihu, and conducted a mixed-methods study to explore user-developed strategies in proposing research-sensemaking questions, and their potential effects on public engagement and knowledge construction. Through open coding, we captured a comprehensive taxonomy of question-crafting strategies, such as eyecatching narratives with counter-intuitive claims and rigorous descriptions with data use. Regression analysis indicated that these strategies correlated with user engagement and answer construction in different ways (e.g., emotional questions attracted more views and answers), yet there existed a general divergence between wide participation and quality knowledge establishment, when most questioning strategies could not ensure both. Based on log analysis, we further found that collaborative editing afforded unique values in refining research-sensemaking questions regarding accuracy, rigor, comprehensiveness and attractiveness. We propose design implications to facilitate accessible, accurate and engaging science communication on CQA platforms.

翻译：在社区问答平台上讨论研究理解类问题已成为公众参与科学传播的常见实践。然而，用户如何策略性地设计研究理解问题以吸引公众参与并促进知识建构，仍是一个重要但未被充分理解的问题。为填补这一研究空白，我们从知乎收集了837个科学相关问题和157,684条回答，采用混合方法探究用户在提出研究理解问题时采用的策略及其对公众参与和知识建构的潜在影响。通过开放式编码，我们捕捉到了问题设计策略的全面分类体系，例如包含反直觉主张的吸睛叙事和运用数据的严谨描述。回归分析表明，这些策略以不同方式与用户参与度和答案建构相关（例如，情感化问题能吸引更多浏览量和回答），但多数提问策略难以同时确保广泛参与和高质量知识建构，两者之间存在普遍分歧。基于日志分析，我们进一步发现协作编辑在优化研究理解问题的准确性、严谨性、全面性和吸引力方面具有独特价值。我们提出设计启示，以促进社区问答平台上可及、准确且引人入胜的科学传播。