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: 10453988
• 负责人: DOLORES ALBARRACIN
• 金额: $ 58.46万
• 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 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10453988
• 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.

项目摘要 SARS-COV-2在美国的传播通过成功进行的方法创造了新的问题 使用尖端的父母赠款，大数据技术来处理大量和多样化的数据（文本，视频， 图像）选择与HIV生物医学需求相匹配的可操作且可接受的社交媒体HIV消息 目标美国县。这些问题包括：（a）我们当前选择的消息与 大流行和当前机器学习方法的背景需要数月才能进行优化； （b） 组合SARS-COV-2/HIV消息是必要的，但是生产它们的方法并非 发达; （c）尚未验证稀缺或新消息的方法。这种紧急 - 补充应用程序请求资源来抵消这些问题，并利用机会生成 关于艾滋病毒的新知识和对大流行的反应。我们的新方法将成功使用同样的方法 测试的技术以选择，生成和传递有关艾滋病毒的组合消息（即测试，准备和 避孕套的使用）以及有关SARS-COV-2的社会距离，测试，预防和治疗的信息， 专门针对与男性发生性关系的男性（MSM）。当前的大流行也提醒您 MSM缺乏疫苗接种；因此，补充项目将整合有关疫苗的消息传递， 包括最终对阵Sars-Cov-2的比赛。抵消不足所带来的新问题 SARS-COV-2次适当的艾滋病毒消息数量，并适应当前的方法 在这种变化的环境中，我们需要（1）新的，快速的方法 识别可操作和可接受的消息； （2）将HIV建议与 与SARS-COV-2有关的新兴公共卫生建议； （3）快速乘以的新方法 社交媒体的结果。因此，此资金申请将遵循以下内容：AIM 1。 目前确定与SARS-COV-2大流行和疫苗有关的区域需求的方法，AIM 2。 为大流行而部署新的消息选择方法，目标3。 通过发送（a）选定的实验消息（与链接结合到 本地服务信息）向社交媒体帐户的管理者和（b）随机选择 HIV/SARS-COV-2消息给一组控制县。这个重要而创新的项目将是 由沟通和说服力，大数据方法，公共卫生和 贝叶斯时空建模，并通过领先机构在心理学领域的参与， 公共卫生和计算机科学。该项目与与之相关的新数据收集工作是协同的 美国男性互联网调查，该调查现在将收集SARS-COV-2血清阳性数据，这将是 补充以对本应用程序提出的项目进行其他行为数据。