In this work we classified subgenres of German novels using different feature sets (mfw 3000, 4gram, lda etc.). Some subgenres, like adventure novels, are much easier to classify than others. Most of the applied feature sets showed a varying but comparable performance except the network features. The weak performance of network features might be caused by the weak link between the novel genre and character constellation. The variability of the subgenre signal could not be countered by using higher level features like topics and network characteristics. Interestingly, the author signal has a strong influence on the classification quality. The strength of influence seems to depend on category but is visible in all experiments. In the future, we would like to extend our work by using different network features, work on advanced topic models and find a reliable indicator for plot. Another challenge we have not faced yet is the development of subgenres over time.