亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Going beyond fact-checking to fight health misinformation: A multi-level analysis of the Twitter response to health news stories

误传 可靠性 社会化媒体 互联网隐私 健康信息 健康传播 假新闻 心理学 公共关系 新闻媒体 广告 政治学 医疗保健 计算机科学 业务 万维网 计算机安全 法学
作者
Bu Zhong
出处
期刊:International Journal of Information Management [Elsevier BV]
卷期号:70: 102626-102626 被引量:14
标识
DOI:10.1016/j.ijinfomgt.2023.102626
摘要

Health misinformation has become an unfortunate truism of social media platforms, where lies could spread faster than truth. Despite considerable work devoted to suppressing fake news, health misinformation, including low-quality health news, persists and even increases in recent years. One promising approach to fighting bad information is studying the temporal and sentiment effects of health news stories and how they are discussed and disseminated on social media platforms like Twitter. As part of the effort of searching for innovative ways to fight health misinformation, this study analyzes a dataset of more than 1600 objectively and independently reviewed health news stories published over a 10-year span and nearly 50,000 Twitter posts responding to them. Specifically, it examines the source credibility of health news circulated on Twitter and the temporal, sentiment features of the tweets containing or responding to the health news reports. The results show that health news stories that are rated low by experts are discussed more, persist longer, and produce stronger sentiments than highly rated ones in the tweetosphere. However, the highly rated stories retained a fresh interest in the form of new tweets for a longer period. An in-depth understanding of the characteristics of health news distribution and discussion is the first step toward mitigating the surge of health misinformation. The findings provide insights into understanding the mechanism of health information dissemination on social media and practical implications to fight and mitigate health misinformation on digital media platforms.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
感动的沛槐完成签到,获得积分10
43秒前
明寒发布了新的文献求助10
1分钟前
chanler完成签到,获得积分10
1分钟前
明寒发布了新的文献求助10
2分钟前
Yodebef完成签到,获得积分20
2分钟前
Yodebef发布了新的文献求助10
2分钟前
2分钟前
小二郎应助科研通管家采纳,获得10
2分钟前
shark完成签到,获得积分10
2分钟前
3分钟前
3分钟前
3分钟前
3分钟前
斯文宛秋发布了新的文献求助10
3分钟前
南岸发布了新的文献求助10
3分钟前
科研通AI6.2应助南岸采纳,获得80
3分钟前
3分钟前
火星上的灵凡完成签到,获得积分10
3分钟前
4分钟前
明寒完成签到,获得积分10
4分钟前
4分钟前
万能图书馆应助Yodebef采纳,获得10
4分钟前
4分钟前
yanglinhai完成签到 ,获得积分10
5分钟前
5分钟前
5分钟前
濮阳娩发布了新的文献求助50
5分钟前
Bin_Liu发布了新的文献求助10
6分钟前
忘忧Aquarius完成签到,获得积分0
6分钟前
6分钟前
6分钟前
6分钟前
Yodebef发布了新的文献求助10
6分钟前
anke完成签到,获得积分10
6分钟前
7分钟前
烟花应助Yodebef采纳,获得10
7分钟前
Sasha完成签到,获得积分10
7分钟前
7分钟前
蓉蓉全肯定完成签到 ,获得积分10
7分钟前
濮阳娩完成签到,获得积分10
7分钟前
高分求助中
Overcoming Stigma and Bias in Obesity Management 800
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Bounds for Statistical Estimation in Semiparametric Models 500
Climate change and sports: Statistics report on climate change and sports 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6472727
求助须知:如何正确求助?哪些是违规求助? 8276343
关于积分的说明 17646529
捐赠科研通 5552149
什么是DOI,文献DOI怎么找? 2909600
邀请新用户注册赠送积分活动 1886372
关于科研通互助平台的介绍 1737799