CoNewsReader: Supporting Comprehensive Understanding and Raising Critical Thoughts on Social Media News Through Comments

2026-04-30

AI Summary

This study addresses the challenge that ordinary users often struggle to deeply comprehend news content and engage in critical thinking while reading on social media, despite the abundance of diverse perspectives embedded in user comments, which remain underutilized due to a lack of effective support mechanisms. To bridge this gap, the work presents the first systematic exploration of leveraging news comments to foster critical reading, proposing an interaction design paradigm that integrates user-generated content with large language models. The authors developed CoNewsReader, a tool informed by user research, which enhances active reflection through comment filtering, key insight extraction, and generation of guided questions. A controlled experiment (N=24) demonstrated that, compared to a baseline interface, CoNewsReader significantly improves users’ depth of news comprehension, critical thinking performance, and sense of engagement during reading.

Abstract

Critical news reading (CNR), which requires grasping the holistic ideas of and raising critical thoughts on the news, is beneficial yet challenging for general people who usually get information on daily social media. Comments under the news can aid CNR by providing complementary information and other readers' diverse and critical thoughts. However, it is under-investigated how to leverage these comments to support users in CNR. In this paper, we first derive user requirements for a comment-based CNR tool from literature and a formative study (N=12). Then, we develop CoNewsReader, a comment-based interactive CNR tool powered by a large language model. CoNewsReader supports users in grasping the news idea with complementary information from comments, filtering useful comments for CNR, and getting questions generated based on the comments to conduct critical thinking. Our within-subjects study with 24 university students indicates that compared to a baseline news reading interface in social media, participants with CoNewsReader have a more engaging CNR experience and perform better on comprehending the news and raising critical thoughts. We discuss design considerations for supporting reading tasks with user- and machine-generated content.

Problem

• critical news reading
• social media comments
• comprehensive understanding
• critical thinking
• news comprehension

Innovation

• critical news reading
• social media comments
• large language model
• user-generated content
• interactive tool