@inproceedings{34cd4f28a18246358aad0d5dc9cf0603,
title = "Effects of Credibility Indicators on Social Media News Sharing Intent",
abstract = "In recent years, social media services have been leveraged to spread fake news stories. Helping people spot fake stories by marking them with credibility indicators could dissuade them from sharing such stories, thus reducing their amplification. We carried out an online study (N = 1,512) to explore the impact of four types of credibility indicators on people's intent to share news headlines with their friends on social media. We confirmed that credibility indicators can indeed decrease the propensity to share fake news. However, the impact of the indicators varied, with fact checking services being the most effective. We further found notable differences in responses to the indicators based on demographic and personal characteristics and social media usage frequency. Our findings have important implications for curbing the spread of misinformation via social media platforms.",
keywords = "disinformation, facebook, fact-check indicators, fake news, misinformation, news headlines, news sharing, social media",
author = "Waheeb Yaqub and Otari Kakhidze and Brockman, {Morgan L.} and Nasir Memon and Sameer Patil",
note = "Publisher Copyright: {\textcopyright} 2020 Owner/Author.; 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020 ; Conference date: 25-04-2020 Through 30-04-2020",
year = "2020",
month = apr,
day = "21",
doi = "10.1145/3313831.3376213",
language = "English (US)",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
booktitle = "CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems",
}