Fig. 3.

Sequence and word similarity networks. a In sequence similarity networks, sequences and similarities between sequences are represented in a network. Sequences are represented as nodes, and similarities between sequences are represented as edges if they exceed a certain threshold. Since evolutionary processes leave certain traces in the topology of these networks, they can be identified by applying standard network techniques. b Since words can be modeled as sequences of sounds, it is straightforward to create networks which represent the similarity among words. Due to the peculiarities of language evolution, however, similarity measures need to be specifically adapted to linguistic needs. As in biology, linguists start from alignments, as illustrated for words meaning ‘sun’ in five Germanic languages, but specific scoring functions are used