<hi xmlns="http://www.tei-c.org/ns/1.0" rend="bold" style="font-size:12pt">Document classification</hi> <hi xmlns="http://www.tei-c.org/ns/1.0" style="font-size:12pt">: Figure 1 and Figure 2 show the classification results based on topic models of newspaper articles and novel segments, respectively. It can be seen in both figures that the classification results gradually become worse with the increase of the setting of Alpha, regardless of how many topics have been trained. Especially if Alpha is set to greater than 1, the classification results based on topic models with more topics (the blue lines) show a stronger decreasing trend than the results based on topic models with fewer topics (the red lines). In comparison, most F1 scores change less when Alpha is set to a value smaller than 1. However, we can still see that the blue lines start to decrease when the Alpha is raised from 0.5 to 1. The highest F1-score of classifying newspaper articles and novel segments in this test are 0.752 and 0.998, respectively, which do not differ much from the pre-defined baseline based on BoW-model.</hi>