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Long story short: finding health advice with informative summaries on health social media
Aslib Journal of Information Management ( IF 2.6 ) Pub Date : 2019-11-18 , DOI: 10.1108/ajim-02-2019-0048
Yi-Hung Liu , Xiaolong Song , Sheng-Fong Chen

Whether automatically generated summaries of health social media can aid users in managing their diseases appropriately is an important question. The purpose of this paper is to introduce a novel text summarization approach for acquiring the most informative summaries from online patient posts accurately and effectively.,The data set regarding diabetes and HIV posts was, respectively, collected from two online disease forums. The proposed summarizer is based on the graph-based method to generate summaries by considering social network features, text sentiment and sentence features. Representative health-related summaries were identified and summarization performance as well as user judgments were analyzed.,The findings show that awarding sentences without using all the incorporating features decreases summarization performance compared with the classic summarization method and comparison approaches. The proposed summarizer significantly outperformed the comparison baseline.,This study contributes to the literature on health knowledge management by analyzing patients’ experiences and opinions through the health summarization model. The research additionally develops a new mindset to design abstractive summarization weighting schemes from the health user-generated content.

中文翻译:

长话短说:在健康社交媒体上找到内容详尽的健康建议

自动生成的健康社交媒体摘要是否可以帮助用户适当地管理疾病是一个重要的问题。本文的目的是介绍一种新颖的文本摘要方法,以准确,有效地从在线患者帖子中获取最多信息的摘要。有关糖尿病和艾滋病毒帖子的数据集分别来自两个在线疾病论坛。提出的摘要器基于图的方法,通过考虑社交网络功能,文本情感和句子功能来生成摘要。确定了具有代表性的与健康相关的摘要,并分析了摘要性能以及用户判断。研究结果表明,与传统的摘要方法和比较方法相比,在不使用所有合并功能的情况下授予句子会降低摘要性能。拟议的摘要器明显优于比较基准。通过健康摘要模型分析患者的经验和观点,本研究为有关健康知识管理的文献做出了贡献。这项研究还开发了一种新的思维方式,可以根据健康用户生成的内容来设计抽象的摘要加权方案。本研究通过健康总结模型分析患者的经验和观点,为有关健康知识管理的文献做出了贡献。这项研究还开发了一种新的思维方式,可以根据健康用户生成的内容来设计抽象的摘要加权方案。本研究通过健康总结模型分析患者的经验和观点,为有关健康知识管理的文献做出了贡献。这项研究还开发了一种新的思维方式,可以根据健康用户生成的内容来设计抽象的摘要加权方案。
更新日期:2019-11-18
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