This paper investigates that an emerging computerized text analysis technique, word embeddings, can capture cultural and concept change. In this paper, we utilize this technique to quantify temporal dynamics of the concept of happiness between 1979—2021 in China. We first conducted in-depth interviews and thus formed five dimensions that generally represent Chinese people's conception of happiness, including physical need, social support, self-actualization, environment harmony and patriotism. We then used word embeddings to analyze the associations of five dimension with well-being. Results show that the correlation between happiness and physical need declines over time while happiness's correlations with self-actualization and with patriotism go upward obviously. What's more, individualism (“self-actualization”) and collectivism-oriented (“patriotism”) dimension shows a consistent trend, this means that traditional value centerring on family and country interest has also been preserved at present age. Although the harmonious relationship with natural environment has not gotten enough attention in general, it tends to go upward these years. By comparing diachronic changes among five dimensions, this research captures the social economic shifts, e.g., the Reform and Opening-up in the end of 1970s, economic reform since 1992, new millennium of 2000, the new era after 2013. Our method further proves to be valid by showing that changes in the embedding track closely with a series of domestic social surveys. Our research demonstrates the powerful utility of computational text analysis and would facilitate intersection between machine learning and social science.