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Analysis of Influencing Factors of Social Mental Health Based on Big Data

机译:基于大数据的社会心理健康影响因素分析

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Big data is a large-scale rapidly growing database of information. Big data has a huge data size and complexity that cannot be easily stored or processed by conventional data processing tools. Big data research methods have been widely used in many disciplines as research methods based on massively big data analysis have aroused great interest in scientific methodology. In this paper, we proposed a deep computational model to analyze the factors that affect social and mental health. The proposed model utilizes a large number of microblog manual annotation datasets. This huge amount of dataset is divided into six main factors that affect social and mental health, that is, economic market correlation, the political democracy, the management law, the cultural trend, the expansion of the information level, and the fast correlation of the rhythm of life. The proposed model compares the review data of different influencing factors to get the correlation degree between social mental health and these factors.
机译:大数据是一个大规模的快速增长的信息数据库。大数据具有巨大的数据大小和复杂性,无法通过传统数据处理工具轻松存储或处理。大数据研究方法已广泛应用于许多学科,因为基于大规模大数据分析的研究方法引起了对科学方法论的极大兴趣。在本文中,我们提出了深度计算模型,分析了影响社会和心理健康的因素。所提出的模型利用大量微博手册注释数据集。这一大量数据集分为六个主要因素,影响社会和心理健康,即经济市场相关,政治民主,管理法,文化趋势,信息水平的扩张以及快速相关性生命的节奏。拟议的模型比较了不同影响因素的审查数据,以获得社会心理健康与这些因素之间的相关程度。

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