Zipf’s Law in China’s Local Government Work Reports: A 21-year Study Using Natural Language Processing and Regression Analysis

This study presents the first large-scale empirical investigation of Zipf’s Law in Chinese provincial government work reports (2003-2023), utilizing a corpus of 651 reports. Employing natural language processing techniques (including Jieba word segmentation with a custom dictionary) and a double-logarithmic regression model, we analyzed word frequency distributions. Results indicate that while generally conforming to Zipf’s Law, substantial inter-regional and inter-temporal variation exists. This variation may be attributable to factors beyond the scope of this study, such as region-specific policies or the influence of the 18th National Congress of the Communist Party of China. While our findings largely confirm Zipf’s Law’s applicability to this specific corpus, the limitations of this study include potential biases in word segmentation and the exclusion of county-level reports. Future research should address these limitations by incorporating a broader range of administrative levels and conducting cross-cultural comparisons with other countries’ political documents. Further investigation of other quantitative linguistic laws (e.g., Heaps’Law, Menzerath’s Law) within this corpus is also warranted.