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

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。

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.