Analysis of Factors Influencing People's Well-being Based on Multi-source Data Fusion

Abstract

As socialism with Chinese characteristics enters a new era, the people's needs for a better life are growing, and more and more people are starting to pay attention to their own well-being. The issue of well-being has received widespread attention. Traditional well-being questionnaires rely mainly on objective questions, while people's comments can describe their subjective well-being more specifically and in greater detail. This article collects relevant comment data on well-being through open-ended questionnaires, and uses text analysis methods such as Chinese word segmentation and LDA topic modeling to identify the thematic features that affect people's well-being. The logical relationships between the various topics are also organized. On this basis, the results are compared and analyzed with the empirical test results of well-being based on CGSS (2015) social survey data, in order to obtain more comprehensive results through the integration of multi-source data. This provides a useful way to enrich the theoretical and methodological research on well-being.