Collaborative Research: SaTC: CORE: Small: Detecting Accounts Involved in Influence Campaigns on Social Media

协作研究:SaTC:核心:小型:检测参与社交媒体影响力活动的帐户

基本信息

  • 批准号:
    2114407
  • 负责人:
  • 金额:
    $ 28万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-05-01 至 2024-04-30
  • 项目状态:
    已结题

项目摘要

The growing popularity of online social networks has opened the door to false information being disseminated by malicious actors. Hostile nation states are orchestrating disinformation campaigns in the United States with the goal of influencing public discourse or pushing talking points that favor a particular country’s agenda. These campaigns are typically carried out with the help of fake social media accounts known as trolls, which pose as fictitious personas. These trolls interact with each other and with unsuspecting social network users with the goal of polarizing discussion and furthering false narratives. Despite the serious threat that disinformation poses to our society, social networks are struggling to keep up with the threat, resorting to reactive measures that remove malicious accounts after the fact. The goal of this project is to develop techniques able to automatically identify troll accounts on social networks so that they can be more swiftly removed.To carry out this project, the investigators are collecting information about the troll accounts identified by Twitter and Reddit as belonging to several foreign countries’ disinformation campaigns. These data are used to train machine learning algorithms able to automatically identify other troll accounts on Twitter and Reddit. The project follows two parallel research tasks. In the first task, the research team aims to train supervised learning algorithms to learn the typical behavior of known troll accounts, with the goal of identifying more accounts that behave similarly and are therefore part of the same disinformation campaign. Preliminary results show that troll accounts exhibit peculiar interaction patterns that are uncommon in real accounts. In the second task, the researchers will work towards identifying traits that are typical of troll accounts regardless of the campaign that they belong to, and use transfer learning techniques to identify emerging disinformation campaigns. Students are involved at all stages of the research.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.
在线社交网络的日益普及为恶意演员传播的虚假信息打开了大门。敌对的民族国家正在策划美国的虚假宣传运动,目的是影响公众话语或推动有利于特定国家的阿格恩达的谈话要点。这些运动通常是在被称为巨魔的虚假社交媒体帐户的帮助下进行的,这些帐户构成了虚构的角色。这些巨魔相互互动,并与不可思议的社交网络用户进行两极分化的讨论和进一步的虚假叙述。尽管虚假信息对我们的社会构成了严重的威胁,但社交网络仍在努力跟上威胁,诉诸于事实后消除恶意帐户的反应性措施。该项目的目的是开发能够自动识别社交网络上的巨魔帐户的技术,以便可以更快地删除它们。要执行该项目,调查人员正在收集有关Twitter和Reddit确定的巨魔帐户的信息,并属于几个外国国家的虚假信息。这些数据用于训练机器学习算法可以自动在Twitter和Reddit上识别其他巨魔帐户。该项目遵循两个并行的研究任务。在第一项任务中,研究小组旨在培训监督的学习算法,以了解已知巨魔帐户的典型行为,目的是确定更多相似行为的帐户,因此是同一虚假信息运动的一部分。初步结果表明,巨魔帐户展示了真实帐户中罕见的奇特交互模式。在第二任任务中,研究人员将致力于确定巨型帐户典型的特征,而不论其属于运动,并使用转移学习技术来识别新兴的虚假信息运动。该奖项反映了NSF的法定任务,并通过基金会的知识分子优点和更广泛的影响评论标准评估来反映了NSF的法定任务。

项目成果

期刊论文数量(12)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
"I'm a Professor, which isn't usually a dangerous job": Internet-facilitated Harassment and Its Impact on Researchers
“我是一名教授,这通常不是一项危险的工作”:互联网引发的骚扰及其对研究人员的影响
  • DOI:
    10.1145/3476082
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Doerfler, Periwinkle;Forte, Andrea;De Cristofaro, Emiliano;Stringhini, Gianluca;Blackburn, Jeremy;McCoy, Damon
  • 通讯作者:
    McCoy, Damon
"How over is it?" Understanding the Incel Community on YouTube
“怎么样了?”
  • DOI:
    10.1145/3479556
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Papadamou, Kostantinos;Zannettou, Savvas;Blackburn, Jeremy;De Cristofaro, Emiliano;Stringhini, Gianluca;Sirivianos, Michael
  • 通讯作者:
    Sirivianos, Michael
Slapping Cats, Bopping Heads, and Oreo Shakes: Understanding Indicators of Virality in TikTok Short Videos
拍打猫、摇头和奥利奥奶昔:了解 TikTok 短视频中的病毒式传播指标
  • DOI:
    10.1145/3501247.3531551
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Ling, Chen;Blackburn, Jeremy;De Cristofaro, Emiliano;Stringhini, Gianluca
  • 通讯作者:
    Stringhini, Gianluca
TrollMagnifier: Detecting State-Sponsored Troll Accounts on Reddit
  • DOI:
    10.1109/sp46214.2022.9833706
  • 发表时间:
    2021-12
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Mohammad Hammas Saeed;Shiza Ali;Jeremy Blackburn;Emiliano De Cristofaro;Savvas Zannettou;G. Stringhini
  • 通讯作者:
    Mohammad Hammas Saeed;Shiza Ali;Jeremy Blackburn;Emiliano De Cristofaro;Savvas Zannettou;G. Stringhini
There are N Impostors Among Us: Understanding the Effect of State-Sponsored Troll Accounts on Reddit Discussions
我们中间有 N 个冒名顶替者:了解国家资助的巨魔账户对 Reddit 讨论的影响
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Gianluca Stringhini其他文献

A Data Donation Approach for Youth Online Safety
青少年在线安全的数据捐赠方法
  • DOI:
    10.2139/ssrn.4627341
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Afsaneh Razi;Ashwaq Alsoubai;J. Park;Xavier V. Caddle;Shiza Ali;Seunghyun Kim;Gianluca Stringhini;Munmun De Choudhury;Pamela J. Wisniewski
  • 通讯作者:
    Pamela J. Wisniewski
Enabling Contextual Soft Moderation on Social Media through Contrastive Textual Deviation
通过对比文本偏差在社交媒体上实现上下文软审核
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Pujan Paudel;Mohammad Hammas Saeed;Rebecca Auger;Chris Wells;Gianluca Stringhini
  • 通讯作者:
    Gianluca Stringhini
In the Press
在新闻界
  • DOI:
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Gianluca Stringhini
  • 通讯作者:
    Gianluca Stringhini
Enabling Privacy-preserving Multidimensional Network Telemetry with Autoencoders
使用自动编码器实现保护隐私的多维网络遥测
Edinburgh Research Explorer International comparison of bank fraud reimbursement: customer perceptions and contractual terms
爱丁堡研究探索者银行欺诈报销的国际比较:客户认知和合同条款
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Ingolf Becker;Alice Hutchings;Ruba Abu;Ross Anderson;Nicholas Bohm;S. Murdoch;M. A. Sasse;Gianluca Stringhini
  • 通讯作者:
    Gianluca Stringhini

Gianluca Stringhini的其他文献

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{{ truncateString('Gianluca Stringhini', 18)}}的其他基金

Collaborative Research: SaTC: TTP: Medium: iDRAMA.cloud: A Platform for Measuring and Understanding Information Manipulation
协作研究:SaTC:TTP:中:iDRAMA.cloud:测量和理解信息操纵的平台
  • 批准号:
    2247868
  • 财政年份:
    2023
  • 资助金额:
    $ 28万
  • 项目类别:
    Continuing Grant
Collaborative Research: SaTC: CORE: Small: Flanker: Automatically Detecting Lateral Movement in Organizations Using Heterogeneous Data and Graph Representation Learning
协作研究:SaTC:核心:小型:侧翼:使用异构数据和图表示学习自动检测组织中的横向运动
  • 批准号:
    2127232
  • 财政年份:
    2021
  • 资助金额:
    $ 28万
  • 项目类别:
    Standard Grant
CAREER: Towards Data-Driven Methods to Counter Online Aggression
职业:寻找数据驱动的方法来对抗网络攻击
  • 批准号:
    1942610
  • 财政年份:
    2020
  • 资助金额:
    $ 28万
  • 项目类别:
    Continuing Grant
Inferring the Purpose of Network Activities
推断网络活动的目的
  • 批准号:
    EP/N008448/1
  • 财政年份:
    2015
  • 资助金额:
    $ 28万
  • 项目类别:
    Research Grant

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Collaborative Research: SaTC: CORE: Medium: Using Intelligent Conversational Agents to Empower Adolescents to be Resilient Against Cybergrooming
合作研究:SaTC:核心:中:使用智能会话代理使青少年能够抵御网络诱骗
  • 批准号:
    2330940
  • 财政年份:
    2024
  • 资助金额:
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Collaborative Research: SaTC: CORE: Medium: Differentially Private SQL with flexible privacy modeling, machine-checked system design, and accuracy optimization
协作研究:SaTC:核心:中:具有灵活隐私建模、机器检查系统设计和准确性优化的差异化私有 SQL
  • 批准号:
    2317232
  • 财政年份:
    2024
  • 资助金额:
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  • 项目类别:
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Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
  • 批准号:
    2338301
  • 财政年份:
    2024
  • 资助金额:
    $ 28万
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协作研究:SaTC:核心:中:具有灵活隐私建模、机器检查系统设计和准确性优化的差异化私有 SQL
  • 批准号:
    2317233
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Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
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    2338302
  • 财政年份:
    2024
  • 资助金额:
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