  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.
