In this study, the complex-network approaches are employed to investigate the word form networks and the lemma networks extracted from dependency syntactic treebanks of fifteen different languages. The results show that it is possible to classify human languages by means of the main parameters of complex networks. The complex-network approaches can obtain language classifications as precise as achieved by contemporary word order typology. Clustering experiments point to the fact that the difference between the word form networks and the lemma networks can make for a better classification of languages. In short, the dependency syntactic networks can reflect morphological variation degrees and morphological complexity.