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

要旨

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.

著者
Philippe Laban
Salesforce Research, New York, New York, United States
Chien-Sheng Wu
Salesforce AI, Palo Alto, California, United States
Lidiya Murakhovs'ka
Salesforce Research, Toronto, Ontario, Canada
Xiang 'Anthony' Chen
UCLA, Los Angeles, California, United States
Caiming Xiong
Salesforce, Palo Alto, California, United States
論文URL

https://doi.org/10.1145/3544548.3581569

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Communication and Social Good

Hall G2
6 件の発表
2023-04-26 23:30:00
2023-04-27 00:55:00