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IP23-006 VIMP: A Discourse-Aware, Community-Informed Toolkit to Predict Virality and Impact of Vaccine Misinformation Contents

IP23-006 VIMP：一个具有话语感知、社区知情的工具包，用于预测疫苗错误信息内容的病毒性和影响

基本信息

批准号：
10762193
负责人：
MARK Stenius ROBERTS
金额：
$ 100万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2024
资助国家：
美国
起止时间：
2024-02-01 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10762193
关键词：
IP23 006 VIMP Discourse Aware

项目摘要

Project Title: VIMP: A Discourse-Aware, Community-Informed Toolkit to Predict Virality and Impact of Vaccine Misinformation Contents Project Abstract: We will develop a contextually grounded natural language processing (NLP) model and build a toolkit around it to leverage the befit of latest developments in data analytics, network simulations and NLP for increasing vaccine acceptance, vaccination rates and disseminating accurate scientific messages according to community needs. Our final product, VIMP, will be a discourse-aware, community-informed toolkit to predict virality and impact of vaccine misinformation contents. We will use a variety of contextually grounded NLP techniques to design our prediction models and will leverage the benefit of advanced simulation techniques for model training and evaluation. Our team will also engage with a diverse panel of community partners who provide advice on model development and tool building. CDC and its partners could use the tool to rapidly respond to misinformation about vaccines. The model and tool would further increase CDC's and its partners' ability to prioritize which misinformation content to respond to and how to allocate resources at the community level.

项目名称： VIMP：一个话语感知的、社区知情的预测疫苗病毒和影响的工具包错误信息内容项目摘要：我们将开发基于上下文的自然语言处理(NLP)模型并构建工具包利用数据分析、网络模拟和NLP方面的最新发展提高疫苗接种率和接种率，传播准确的科学信息根据社区需求。我们的最终产品VIMP将是一个有话语意识的、社区知情的用于预测疫苗错误信息内容的病毒度和影响的工具包。我们将使用各种基于上下文的NLP技术来设计我们的预测模型，并将利用先进的模拟技术，用于模型训练和评估。我们的团队还将与由社区合作伙伴组成的多样化小组，他们就模型开发和工具构建提供建议。疾控中心它的合作伙伴可以使用该工具对有关疫苗的错误信息做出快速回应。该模型和该工具将进一步提高疾控中心及其合作伙伴对哪些错误信息内容进行优先排序的能力应对并如何在社区一级分配资源。