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.

利用自然语言处理分析了十亿个字，来研究中国最大的社交媒体平台之一微博上的文化差异。比较了关于中国文化差异的两种常见解释（经济发展和城乡差异），并与不那么明显的稻谷种植与小麦种植的遗留影响进行对比。稻谷种植地区使用了更多反映紧密社会关系、整体性思维和谨慎、预防导向的词汇，从而测试这种遗留影响是否使中国南方更加相互依存。通过对日本的推特数据进行比较，得到了与中国几乎相同的结果，从而为稻谷理论提供了重要证据。