课题基金 / 基金详情

CAREER: Enhanced Analysis & Algorithms to Minimize the Spread of Misinformation in Social Networks

CAREER: Enhanced Analysis & Algorithms to Minimize the Spread of Misinformation in Social Networks
职业:增强分析
批准号:
1943370
负责人:
Francesca Spezzano
金额:
$48.75万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-06-01 至 2025-05-31

项目摘要

项目成果

Francesca Spezzano的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
The project goal is to significantly reduce the destructive spread of misinformation on social media and other Web sources, and its potential threat to national security. To do so, the investigator will develop new machine learning algorithms to better detect authenticity and recommend content. The research integrates computer and social sciences to account for the complex real-world interactions among publisher, platform, content recommendation algorithms, bot users, human users, and their social connections. One way social networks engage users is by keeping them consuming personalized content. Malicious actors can easily penetrate these systems with misleading stories and consequent recommendations that prompt people to make decisions based on this misinformation. Younger generations are increasingly active on such platforms, making it critical to reduce the threat that the continuing spread of misinformation poses. Findings will result in a deeper understanding of how recommender systems behave in the presence of misleading stories, and will offer systems design strategies to insure that people receive accurate information to make decisions.There is currently no framework in place to quantify how much recommendations with misinformation in the loop influence social network users. This research will fill this gap. Project objectives are to: (1) develop graph-based models to measure the degree of story, sources, and user credibility as opposed to a typical binary assessment; (2) develop a new framework integrating user-centric information diffusion models to assess the impact of, and compute benchmarks for, current recommender systems in spreading misleading stories; (3) develop algorithms for content recommender systems that will minimize misinformation spread in social networks. An integrated education plan will engage Boise State University college students, who will use a service-learning approach to help Idaho high school students and teachers improve their ability to identify and respond to misinformation. Educational activities will also increase awareness of and interest in computer science occupations, and encourage minorities' retention and diversity.This project is jointly funded by Secure and Trustworthy Cyberspace (SaTC) program and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
Using Service-Learning in Graduate Curriculum to Address Teenagers' Vulnerability to Web Misinformation
在研究生课程中利用服务学习来解决青少年对网络错误信息的脆弱性
DOI: 10.1145/3456565.3460039
发表时间: 2021
期刊: ITiCSE '21: Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 2
影响因子: --
作者: [Spezzano, Francesca]
通讯作者: Spezzano, Francesca
How Do People Decide Political News Credibility?
人们如何决定政治新闻的可信度?
DOI: 10.1109/asonam49781.2020.9381342
发表时间: 2020
期刊: ASONAM 2020
影响因子: --
作者: [Spezzano, Francesca, Winiecki, Don]
通讯作者: Winiecki, Don
DOI: 10.1007/s41060-021-00291-z
发表时间: 2021-11-22
期刊: INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS
影响因子: 2.4
作者: [Shrestha, Anu, Spezzano, Francesca]
通讯作者: Spezzano, Francesca
DOI: 10.1145/3487351.3488345
发表时间: 2021-11
期刊: Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
影响因子: --
作者: [Abishai Joy;Anu Shrestha;Francesca Spezzano]
通讯作者: Abishai Joy;Anu Shrestha;Francesca Spezzano
10
    REU Site: Data-driven Security
    • 批准号:
      1950599
    • 项目类别:
      Standard Grant
    • 资助金额:
      $36.45万
    • 财政年份:
      2020
    • 负责人:
      Francesca Spezzano
    • 依托单位:
    海外基金