Visually and phonologically similar characters are major contributing factors for errors in Chinese text. By defining appropriate similarity measures that consider extended Cangjie codes, we can identify visually similar characters within a fraction of a second. Relying on the pronunciation information noted for individual characters in Chinese lexicons, we can compute a list of characters that are phonologically similar to a given character. We collected 621 incorrect Chinese words reported on the Internet, and analyzed the causes of these errors. 83% of these errors were related to phonological similarity, and 48% of them were related to visual similarity between the involved characters. Generating the lists of phonologically and visually similar characters, our programs were able to contain more than 90% of the incorrect characters in the reported errors.