Zhu and Greenstein then identified some 4,000 articles that appeared in both Encyclopædia Britannica and Wikipedia, and determined how many of each of these code words were included, in an effort to determine overall bias and direction. They found that in general, Wikipedia articles were more biased—with 73 percent of them containing code words, compared to just 34 percent in Britannica. In almost all cases, Wikipedia was more left-leaning than Britannica. Dividing articles into categories, the researchers found, for example, that stories on corporations were 11 percent more slanted toward Democrats, while observing similar leanings on topics such as government (9 percent), education (4 percent), immigration (4 percent), and civil rights (3 percent). Other categories did not have enough data to significantly identify bias.