Mining Social Media Messages for HIV Testing and Prevention Communication

挖掘社交媒体信息以进行艾滋病毒检测和预防沟通

• 批准号: 10480894
• 负责人: DOLORES ALBARRACIN
• 金额: $ 51.43万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10480894
• 关键词: 2019-nCoV; AIDS prevention; Adopted; American; Anti-Retroviral Agents; Area; Behavioral; Big Data; Big Data Methods; COVID-19 pandemic; COVID-19 treatment; COVID-19 vaccination; Communication; Communities; Consumption; County; Data; Data Collection; Discrimination; Emergency Situation; Environment; Epidemic; Facebook; Funding; HIV; Harm Reduction; Health; Health Promotion; Health Sciences; Health system; Home; Human Papillomavirus; Human immunodeficiency virus test; Image; Information Services; Injecting drug user; Institution; Internet; Knowledge; Link; Methods; Mining; Modeling; Persuasive Communication; Population; Prejudice; Prevention; Psychology; Public Health; Published Comment; Random Allocation; Recommendation; Request for Applications; Research; Resources; Savings; Seroprevalences; Social Distance; Source; Surveys; Techniques; Testing; Text; Time; Twitter; United States; Vaccination; Vaccines; analytical method; arm; base; computer science; condoms; design; digital media; diverse data; evidence base; experimental study; fighting; flexibility; flu; innovation; machine learning method; men; men who have sex with men; novel; novel strategies; pandemic disease; parent grant; pre-exposure prophylaxis; programs; rapid technique; response; service programs; social; social media; spatiotemporal; syntax

PROJECT SUMMARY The spread of the SARS-CoV-2 in the US has created novel problems with methods successfully underway in the parent grant that use cutting edge, Big Data techniques for processing vast and diverse data (text, videos, images) to select actionable and acceptable social media HIV messages that match the HIV biomedical needs of target US counties. These problems include: (a) the messages we are currently selecting are not relevant in the context of the pandemic and the current machine learning methods take many months to optimize; (b) combination SARS-CoV-2/HIV messages would be necessary but the methods to produce them have not been developed; and (c) no methods to multiply scarce or new messages have been validated. This emergency- supplement application requests the resources to offset these problems and to use the opportunity to generate new knowledge about HIV and responses to pandemics. Our new approach will use the same successfully tested techniques to select, generate, and deliver combination messages about HIV (i.e., testing, PrEP, and condom use) and messages about social distancing, testing, prevention, and treatment of the SARS-CoV-2, specifically for Men who have Sex with Men (MSM). The current pandemic also serves as a reminder that vaccination is lacking in MSM; therefore, the supplemental project will integrate messaging about vaccines, including an eventual one against SARS-CoV-2. To counteract the new problems resulting from insufficient numbers of appropriate HIV messages for the SARS-CoV-2 times and to adapt current methods which are too time-consuming and inflexible for messaging in such a changing environment, we need (1) new, rapid methods to identify actionable and acceptable messages; (2) new methods to combine HIV recommendations with emerging public health recommendations related to SARS-CoV-2; and (3) new methods to rapidly multiply the resulting messages for social media. Thus, this funding application will pursue the following: Aim 1. Extend current methods to identify regional needs related to the SARS-CoV-2 pandemic and vaccines, Aim 2. Deploy new rapid methods of message selection for a pandemic, and Aim 3. Experimentally test the effect of the new methods by sending (a) the selected experimental messages (combined with links to local service information) to managers of social media accounts and (b) a random selection of HIV/SARS-CoV-2 messages to a group of control counties. This significant and innovative project will be facilitated by unique team expertise in communication and persuasion, Big Data methods, public health, and Bayesian spatio-temporal modeling, and by the participation of leading institutions in the areas of psychology, public health, and computer science. The project is synergistic with new data collection efforts associated with the American Men Internet Survey, which will now collect SARS-CoV-2 seroprevalence data, which will be supplemented to conduct additional behavioral data for the project proposed in this application.

项目概要 SARS-CoV-2 在美国的传播给美国成功实施的方法带来了新的问题 家长资助使用尖端的大数据技术来处理大量多样的数据（文本、视频、 图像）来选择符合艾滋病毒生物医学需求的可行且可接受的社交媒体艾滋病毒信息 美国目标县的数量。这些问题包括： (a) 我们当前选择的消息与 大流行的背景和当前的机器学习方法需要几个月的时间来优化； (二) SARS-CoV-2/HIV 信息的组合是必要的，但生成它们的方法尚未确定 发达; (c) 尚未验证任何繁殖稀有或新信息的方法。这次紧急情况—— 补充申请请求资源来抵消这些问题并利用机会产生 关于艾滋病毒和应对流行病的新知识。我们的新方法将成功地使用相同的方法 经过测试的技术来选择、生成和传递有关 HIV 的组合信息（即测试、PrEP 和 使用安全套）以及有关 SARS-CoV-2 的社交距离、检测、预防和治疗的信息， 专门针对男男性行为者 (MSM)。当前的疫情也提醒我们 MSM 缺乏疫苗接种；因此，补充项目将整合有关疫苗的信息， 包括最终针对 SARS-CoV-2 的一种。应对因资源不足而产生的新问题 SARS-CoV-2 时代的适当 HIV 信息数量，并适应当前的方法，这些方法太 在这样一个不断变化的环境中，消息传递既耗时又不灵活，我们需要 (1) 新的、快速的方法 识别可操作且可接受的消息； (2) 将艾滋病毒建议与 与 SARS-CoV-2 相关的新公共卫生建议； (3) 快速繁殖的新方法 由此产生的社交媒体消息。因此，本次资助申请将追求以下目标： 目标 1. 扩展 当前确定与 SARS-CoV-2 大流行和疫苗相关的区域需求的方法，目标 2。 部署针对流行病的新的快速消息选择方法，目标 3。通过实验测试 通过发送（a）选定的实验消息（结合链接到 本地服务信息）发送给社交媒体帐户的管理员，以及（b）随机选择 向一组对照县发送 HIV/SARS-CoV-2 信息。这一重大且创新的项目将 凭借在沟通和说服、大数据方法、公共卫生和 贝叶斯时空建模，以及心理学领域领先机构的参与， 公共卫生和计算机科学。该项目与新的数据收集工作具有协同作用 美国男性互联网调查，现在将收集 SARS-CoV-2 血清流行率数据，这些数据将 补充以为本申请中提出的项目进行额外的行为数据。