We used natural language processing to analyze a billion words to study cultural differences on Weibo, one of China's largest social media platforms. We compared predictions from two common explanations about cultural differences in China (economic development and urban-rural differences) against the less-obvious legacy of rice versus wheat farming. Rice farmers had to coordinate shared irrigation networks and exchange labor to cope with higher labor requirements. In contrast, wheat relied on rainfall and required half as much labor. We test whether this legacy made southern China more interdependent. Across all word categories, rice explained twice as much variance as economic development and urbanization. Rice areas used more words reflecting tight social ties, holistic thought, and a cautious, prevention orientation. We then used Twitter data comparing prefectures in Japan, which largely replicated the results from China. This provides crucial evidence of the rice theory in a different nation, language, and platform.

翻译：我们运用自然语言处理技术分析数十亿字词，研究中国最大社交媒体平台之一微博上的文化差异。将两种关于中国文化差异的常见解释（经济发展与城乡差异）与相对隐蔽的水稻与小麦种植传统进行比较。水稻农民需要协调共享灌溉网络并交换劳动力以应对更高的劳动需求，而小麦种植依赖降雨且所需劳动力仅为水稻的一半。我们验证了这种传统是否使中国南方地区更具相互依存性。在所有词类中，水稻种植模式解释的方差是经济发展和城市化的两倍。水稻种植区使用更多反映紧密社会纽带、整体思维以及谨慎预防导向的词汇。随后我们利用日本各都道府县的推特数据进行验证，结果与中国基本一致。这为水稻理论在不同国家、语言和平台中的适用性提供了关键证据。