找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Disinformation, Misinformation, and Fake News in Social Media; Emerging Research Ch Kai Shu,Suhang Wang,Huan Liu Book 2020 Springer Nature

[复制链接]
楼主: Lipase
发表于 2025-3-28 15:01:35 | 显示全部楼层
Systems Collaboration and Integration does the audience engage with mis- and dis-information?, and (3) What feedback do users provide? These patterns and insights can be leveraged to develop better strategies to improve media literacy and informed engagement with crowd-sourced information like social news.
发表于 2025-3-28 22:07:30 | 显示全部楼层
发表于 2025-3-28 23:36:19 | 显示全部楼层
发表于 2025-3-29 03:47:12 | 显示全部楼层
Barrett S. Caldwell,P. U. Grouperopic group analysis and Twitter-Youtube networks, we also show that all of the campaigns originated in similar communities. This informs future work focused on the cross-platform and cross-network nature of these conversations with an eye toward how that may improve our ability to classify the intent and effect of various campaigns.
发表于 2025-3-29 09:28:40 | 显示全部楼层
发表于 2025-3-29 15:04:16 | 显示全部楼层
发表于 2025-3-29 19:17:54 | 显示全部楼层
https://doi.org/10.1007/978-3-030-33312-6 training the model, we construct a million scale dataset of news articles, which we also release for broader research use. Based on the results of a focus group interview, we discuss the importance of developing an interpretable AI agent for the design of a better interface for mitigating the effects of online misinformation.
发表于 2025-3-29 22:36:52 | 显示全部楼层
Pretending Positive, Pushing False: Comparing Captain Marvel Misinformation Campaignsopic group analysis and Twitter-Youtube networks, we also show that all of the campaigns originated in similar communities. This informs future work focused on the cross-platform and cross-network nature of these conversations with an eye toward how that may improve our ability to classify the intent and effect of various campaigns.
发表于 2025-3-30 02:16:49 | 显示全部楼层
发表于 2025-3-30 07:31:31 | 显示全部楼层
Developing a Model to Measure Fake News Detection Literacy of Social Media Usersis empirically tested by applying correlation analyses based on a sample of . = 96. The updated construct provides a way to measure fake news detection literacy and offers various avenues for further research that are discussed at the end of the chapter.
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-25 04:12
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表