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We introduce a method to convert an ensemble of sequences of symbols into a weighted directed network whose nodes are motifs, while the directed links and their weights are defined from statistically significant co-occurences of two motifs in the same sequence. The analysis of communities of networks of motifs is shown to be able to correlate sequences with functions in the human proteome database, to detect hot topics from online social dialogs, to characterize trajectories of dynamicaldoi:10.1103/physrevlett.105.178702 pmid:21231087 fatcat:t5vzcr5yjngfvo6wt6wbwqbqyu