English

Designing and Evaluating Interfaces that Highlight News Coverage Diversity Using Discord Questions

Human-Computer Interaction 2023-02-20 v1 Computation and Language

Abstract

Modern news aggregators do the hard work of organizing a large news stream, creating collections for a given news story with tens of source options. This paper shows that navigating large source collections for a news story can be challenging without further guidance. In this work, we design three interfaces -- the Annotated Article, the Recomposed Article, and the Question Grid -- aimed at accompanying news readers in discovering coverage diversity while they read. A first usability study with 10 journalism experts confirms the designed interfaces all reveal coverage diversity and determine each interface's potential use cases and audiences. In a second usability study, we developed and implemented a reading exercise with 95 novice news readers to measure exposure to coverage diversity. Results show that Annotated Article users are able to answer questions 34% more completely than with two existing interfaces while finding the interface equally easy to use.

Keywords

Cite

@article{arxiv.2302.08997,
  title  = {Designing and Evaluating Interfaces that Highlight News Coverage Diversity Using Discord Questions},
  author = {Philippe Laban and Chien-Sheng Wu and Lidiya Murakhovs'ka and Xiang 'Anthony' Chen and Caiming Xiong},
  journal= {arXiv preprint arXiv:2302.08997},
  year   = {2023}
}

Comments

CHI2023 Accepted Paper

R2 v1 2026-06-28T08:42:56.244Z