FeedReflect: A Tool for Nudging Users to Assess News Credibility on Twitter

被引：39

作者：

Bhuiyan, Md Momen ^{[1
]}

Zhang, Kexin ^{[2
]}

Vick, Kelsey ^{[1
]}

Horning, Michael A. ^{[1
]}

Mitra, Tanushree ^{[1
]}

机构：

[1] Virginia Tech, Blacksburg, VA 24061 USA

[2] Georgia Tech, Atlanta, GA 30332 USA

来源：

COMPANION OF THE 2018 ACM CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING (CSCW'18) | 2018年

关键词：

Social Media; News Credibility; User engagement; Reflection; FeedReflect;

D O I：

10.1145/3272973.3274056

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In recent years, the emergence of fake news outlets has drawn out the importance of news literacy. This is particularly critical in social media where the flood of information makes it difficult for people to assess the veracity of the false stories from such deceitful sources. Therefore, people oftentimes fail to look skeptically at these stories. We explore a way to circumvent this problem by nudging users into making conscious assessments of what online contents are credible. For this purpose, we developed FeedReflect, a browser extension. The extension nudges users to pay more attention and uses reflective questions to engage in news credibility assessment on Twitter. We recruited a small number of university students to use this tool on Twitter. Both qualitative and quantitative analysis of the study suggests the extension helped people accurately assess the credibility of news. This implies FeedReflect can be used for the broader audience to improve online news literacy.

引用

页码：205 / 208

页数：4