幸福感数据集

在社会科学领域，幸福感的研究占有重要的位置。这个涉及了哲学、心理学、社会学、经济学等多方学科的话题复杂而有趣；同时与大家生活息息相关，每个人对幸福感都有自己的衡量标准。如果能发现影响幸福感的共性，生活中是不是将多一些乐趣；如果能找到影响幸福感的政策因素，便能优化资源配置来提升国民的幸福感。目前社会科学研究注重变量的可解释性和未来政策的落地，主要采用了线性回归和逻辑回归的方法，在收入、健康、职业、社交关系、休闲方式等经济人口因素；以及政府公共服务、宏观经济环境、税负等宏观因素上有了一系列的推测和发现。 赛题尝试了幸福感预测这一经典课题，希望在现有社会科学研究外有其他维度的算法尝试，结合多学科各自优势，挖掘潜在的影响因素，发现更多可解释、可理解的相关关系

In the field of social sciences, research on happiness holds a prominent position. This topic, which spans multiple disciplines including philosophy, psychology, sociology, economics and others, is both complex and fascinating, and is also closely tied to people’s daily lives—every individual has their own criteria for measuring happiness. If we can identify the common factors influencing happiness, we could bring more joy to daily life; if we can uncover policy-related factors affecting happiness, we can optimize resource allocation to improve national well-being. Currently, social science research prioritizes the interpretability of variables and the practical implementation of future policies, mainly adopting linear regression and logistic regression methods. A series of inferences and findings have been derived from analyses of socioeconomic-demographic factors such as income, health, occupation, social relationships and leisure habits, as well as macro-level factors including government public services, macroeconomic environment and tax burden. This task addresses the classic topic of happiness prediction, aiming to conduct algorithmic explorations from novel dimensions beyond existing social science research, integrate the respective strengths of multiple disciplines, excavate potential influencing factors, and discover more interpretable and understandable correlational relationships.

搜集汇总

背景与挑战

背景概述

幸福感数据集是一个用于研究幸福感影响因素的公共数据集，来源于中国人民大学中国调查与数据中心的《中国综合社会调查（CGSS）》，采用多阶分层抽样的截面面访调查方法。数据集包含个体变量（如性别、年龄、职业）、家庭变量（如父母、家庭资本）和社会态度变量（如公平、信用），旨在通过数据挖掘预测幸福感评价，并分为完整版和精简版以方便分析。