Social networks are rich source of data to analyze user habits in all aspects of life. User's behavior is decisive component of a health system in various countries. Promoting good behavior can improve the public health significantly. In this work, we develop a new model for social network analysis by using text analysis approach. We define each user reaction to global pandemic with analyzing his online behavior. Clustering a group of online users with similar habits, help to find how virus spread in different societies. Promoting the healthy life style in the high risk online users of social media have significant effect on public health and reducing the effect of global pandemic. In this work, we introduce a new approach to clustering habits based on user activities on social media in the time of pandemic and recommend a machine learning model to promote health in the online platforms.

中文翻译：

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社交网络分析以检索在线平台上的批评意见

社交网络是分析生活各个方面用户习惯的丰富数据源。用户行为是各个国家卫生系统的决定性组成部分。提倡良好的行为习惯可以大大改善公共健康。在这项工作中，我们使用文本分析方法开发了一种用于社交网络分析的新模型。我们通过分析其在线行为来定义每个用户对全球大流行的反应。将一群具有相似习惯的在线用户聚集在一起，有助于发现病毒在不同社会中的传播方式。在社交媒体的高风险在线用户中推广健康的生活方式，对公共健康具有重大影响，并减少了全球大流行的影响。在这项工作中，