Collaborative Research: SaTC: CORE: Small: Understanding how visual features of misinformation influence credibility perceptions

协作研究：SaTC：核心：小：了解错误信息的视觉特征如何影响可信度认知

基本信息

批准号：
2150723
负责人：
Yilang Peng
金额：
$ 21.5万
依托单位：
University of Georgia Research Foundation Inc
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2150723&HistoricalAwards=false
关键词：
Collaborative Research SaTC CORE Small

项目摘要

Today’s misinformation posts have increasingly been presented in visual formats, such as images, memes, and videos. Compared to text, visuals are processed faster, remembered better, and are more likely to be shared on social media. As technology makes image and video manipulation accessible to the masses, visual misinformation can be a significant threat to national security, social cohesion, and public health. Yet we need to know more about how specific visual features, such as color and face presence, may influence how people evaluate the credibility of such visual posts. This project offers a comprehensive understanding of how different visual elements may influence users’ perceived credibility of images and videos. The results help platforms and fact-checking agencies to detect visual misinformation, curb its diffusion, identify vulnerable user groups, and develop corrective interventions.Drawing broadly from literature in computer science, advertising, marketing, cognitive science, and communication, and using computer vision analysis, qualitative interviews, large-scale human annotation, and experiments, this research project aims to: 1) identify the specific visual features and mechanisms which may influence people’s credibility perceptions, 2) examine how these visual features interact with non-visual features (source, virality, etc) and user characteristics (partisanship, digital media literacy, etc), and 3) examine how these visual features can be effectively leveraged in misinformation correction efforts. The research team is compiling a large-scale open dataset of visual posts with human annotations. While existing misinformation datasets have largely focused on the veracity of messages, this dataset provides credibility perceptions along with other relevant outcomes such as attention, emotional reactions and aesthetic appeal. In addition, the research team is creating a website with accessible information to educate the general public about misinformation presented in images and videos, so that the public can be aware of their vulnerabilities and be more vigilant towards certain types of visual information.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.

如今，以视觉格式（例如图像，模因和视频）呈现了今天的错觉帖子。与文本相比，视觉效果的处理速度更快，被记住更好，并且更有可能在社交媒体上共享。由于技术使大众可以访问图像和视频操纵，因此视觉错误信息可能对国家安全，社会凝聚力和公共卫生构成重大威胁。但是，我们需要更多地了解特定视觉特征（例如颜色和面部的存在）如何影响人们评估此类视觉帖子的信誉。该项目对不同的视觉元素如何影响用户对图像和视频的可信度有了全面的了解。这些结果有助于平台和事实检查机构检测视觉错误信息，遏制其差异，确定脆弱的用户群体并制定纠正性干预措施。从计算机科学，广告，广告，营销，认知科学和沟通以及使用计算机视觉分析，使用定性访谈，大规模的人类概念和实验性的项目的特定机构和实验性的范围和实验性的范围的特定机构，从而广泛地从文学中汲取灵感：1）可信度感知，2）检查这些视觉特征如何与非视觉特征（源，病毒性等）和用户特征（Partisisship，数字媒体素养等）相互作用，并且3）研究如何在错觉校正校正工作中有效利用这些视觉特征。研究团队正在用人类注释编辑大规模的视觉帖子数据集。尽管现有的错觉数据集主要集中在消息的真实性上，但该数据集提供了信誉感知以及其他相关结果，例如注意力，情感反应和美学吸引力。此外，研究团队正在创建一个带有可访问信息的网站，以向公众教育图像和视频中呈现的错觉，以便公众可以意识到其脆弱性，并更加警惕某些类型的视觉信息。该奖项反映了NSF的法定任务，并认为通过基金会的知识优点和广泛的影响，通过评估来获得珍贵的支持。