Using social networks to predict changes in health: Extended abstract

Karen S. Jung, O. Tonguz
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引用次数: 0

Abstract

Social networking sites not only have billions of users but detailed content about each individual's daily life. This detailed information about a person's life could be exploited to allow individuals to learn more about themselves. In this paper, we introduce the concept of using social networks to foresee changes in an individual's health. We develop a new model that can predict if a person has recently undergone weight loss by analyzing the text from the person's tweets. Sentiment analysis, parts-of-speech (POS) tagging, and categorization are used in this model. The model is tested on Twitter users and a good statistical accuracy is observed. The success of this model suggests that this idea could be further explored to identify other patterns and create new models for a variety of health changes and health problems, particularly those that are of huge interest to individuals and businesses.
利用社会网络预测健康变化:扩展摘要
社交网站不仅拥有数十亿用户,还拥有每个人日常生活的详细内容。这些关于一个人生活的详细信息可以被利用,让个人更多地了解自己。在本文中,我们引入了使用社交网络来预测个人健康变化的概念。我们开发了一个新模型,可以通过分析一个人的推文来预测他最近是否在减肥。该模型使用了情感分析、词性标注和分类。该模型在Twitter用户上进行了测试,并观察到良好的统计准确性。这一模式的成功表明,可以进一步探索这一想法,以确定其他模式,并为各种健康变化和健康问题,特别是那些个人和企业非常感兴趣的问题,创建新的模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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