CoNewsReader: Supporting Comprehensive Understanding and Raising Critical Thoughts on Social Media News Through Comments
Kangyu Yuan, Guanzheng Chen, Sizhe Liang, Hehai Lin, Qingyu Guo + 3 more
TLDR
CoNewsReader uses comments and AI to enhance critical news reading and understanding on social media.
Key contributions
- Identified user needs for comment-based critical news reading tools.
- Developed CoNewsReader, an AI-powered tool integrating comments for deeper news comprehension.
- Supports filtering comments and generating critical questions to boost engagement.
- User study shows improved news understanding and critical thinking with CoNewsReader.
Why it matters
This paper addresses the challenge of critical news reading on social media by leveraging comments and AI. It offers a novel tool that enhances comprehension and critical engagement, helping users navigate complex news contexts effectively.
Original 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.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.