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Detecting ADRD Caregivers’ Information Wants in Social Media: A Machine Learning–Aided Approach

机译:检测Adrd Caregiers的信息需要在社交媒体中:机器学习辅助方法

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摘要

ADRD caregivers increasingly use social media to meet their health information wants (HIW). Machine learning (ML) tools may help understand caregivers’ HIW as expressed via social media. This pilot study explored a collaborative, iterative process between domain experts and ML tools to identify ADRD caregivers’ HIW from social media data. The HIW-ADRD framework was adapted from an existing HIW framework. Through multiple rounds of iteration between the experts and the ML tools, the framework was expanded to include 11 types of health information. Each type included corresponding keywords developed through a hybrid approach that included keywords from both the theoretical constructs (top-down) and caregivers’ posts (bottom-up). These keywords were then used to enhance the ML tools’ ability to code 106 recent posts extracted from an ADRD social media group in March 2020. When compared with expert coding results, ML tools accurately predicted 56% of HIW. Further work is underway.
机译:ADRD护理人员越来越使用社交媒体来满足他们的健康信息(HIW)。机器学习(ML)工具可以帮助了解通过社交媒体表达的护理人员。该试点研究探讨了域专家和ML工具之间的协同,迭代过程,以识别来自社交媒体数据的ADRD Caregiers的HIW。 HIW-ADRD框架是从现有的HIW框架改编。通过专家和ML工具之间的多轮迭代,框架被扩展到包括11种类型的健康信息。每种类型包括通过混合方法开发的相应关键字,其中包含来自理论构造(自上而下)和护理人员帖子(自下而上)的关键字。然后使用这些关键字来增强ML Tools的能力,以2020年3月在ADRD社交媒体组中提取的106个帖子的能力。与专家编码结果相比,ML工具准确地预测了56%的HIW。正在进行进一步的工作。

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