找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

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

[復(fù)制鏈接]
樓主: Lipase
41#
發(fā)表于 2025-3-28 15:01:35 | 只看該作者
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.
42#
發(fā)表于 2025-3-28 22:07:30 | 只看該作者
43#
發(fā)表于 2025-3-28 23:36:19 | 只看該作者
44#
發(fā)表于 2025-3-29 03:47:12 | 只看該作者
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.
45#
發(fā)表于 2025-3-29 09:28:40 | 只看該作者
46#
發(fā)表于 2025-3-29 15:04:16 | 只看該作者
47#
發(fā)表于 2025-3-29 19:17:54 | 只看該作者
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.
48#
發(fā)表于 2025-3-29 22:36:52 | 只看該作者
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.
49#
發(fā)表于 2025-3-30 02:16:49 | 只看該作者
50#
發(fā)表于 2025-3-30 07:31:31 | 只看該作者
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.
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-11 13:48
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
青川县| 呼图壁县| 常熟市| 青岛市| 井研县| 盈江县| 墨脱县| 惠来县| 金沙县| 张家界市| 湘阴县| 黄浦区| 耿马| 始兴县| 蛟河市| 金华市| 微博| 东莞市| 茶陵县| 中江县| 古交市| 洪雅县| 阿拉善右旗| 五华县| 稷山县| 潮州市| 定边县| 大庆市| 镇康县| 甘孜| 浦城县| 荥经县| 墨竹工卡县| 合山市| 黄龙县| 北京市| 新巴尔虎右旗| 资溪县| 施甸县| 大厂| 泊头市|