{'fraction_non_alphanumeric': 0.0334855403348554, 'fraction_numerical': 0.0091324200913242, 'mean_word_length': 4.483333333333333, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Language as a Small World Network

Small world networks are graphs, which integrate the properties of random graphs and lattice graphs [5]. Several real networks can be modeled with a help of small worlds [1, 2, 6, 8]. As shown in this paper a word web has small world structure too. We have shown, that different languages, such as Slovak and English, have similar small world properties. As our second goal, we built a graph on the basis of kernel lexicon words, in order to test the scaling results of Cancho and Sol¿ [6]. We speculate that the differences between calculated and measured exponents of connectivity distribution are due to the node aging.