A team of researchers at UC Berkeley and China Digital Times have dedicated their efforts in analyzing the Chinese government's motivations, collecting keywords and articles that are proven to be censored in China.
Identified keywords are censored on Weibo and are logged and tested over time. Researchers find pairings and combinations of the keywords to help build a more nuanced understanding of the sensitive topics of interest.
The China Digital Times captures removed content on their server. Our team reviewed the top articles by visitors since April 2012 and have identified content of interest to serve to our readers in this visualization.
Our team organized the articles into 4 categories and utilized a term-document frequency algorithm (tf-idf) to highlight the censored keywords that are of greatest importance to this identified corpus.