The disparity between news stories valued by journalists and those preferred by readers, known as the "News Gap", is well-documented. However, the difference in expectations regarding news related user-generated content is less studied. Comment sections, hosted by news websites, are popular venues for reader engagement, yet still subject to editorial decisions. It is thus important to understand journalist vs reader comment preferences and how these are served by various comment ranking algorithms that represent discussions differently. We analyse 1.2 million comments from Austrian newspaper Der Standard to understand the "News Comment Gap" and the effects of different ranking algorithms. We find that journalists prefer positive, timely, complex, direct responses, while readers favour comments similar to article content from elite authors. We introduce the versatile Feature-Oriented Ranking Utility Metric (FORUM) to assess the impact of different ranking algorithms and find dramatic differences in how they prioritise the display of comments by sentiment, topical relevance, lexical diversity, and readability. Journalists can exert substantial influence over the discourse through both curatorial and algorithmic means. Understanding these choices' implications is vital in fostering engaging and civil discussions while aligning with journalistic objectives, especially given the increasing legal scrutiny and societal importance of online discourse.

本研究探讨了新闻记者与读者在用户生成内容评论偏好上的差异，即“新闻评论差距”。通过分析120万个评论，我们引入了一种名为FORUM的排名效用度量，发现记者倾向于积极、及时、复杂的评论，而读者则更喜欢内容相关的评论。研究结果揭示了不同排名算法的显著影响，强调了在促进公正讨论和回应新闻目标中的重要性。

新闻评论差距与在线论坛中的算法议程设置