{'fraction_non_alphanumeric': 0.015891032917139614, 'fraction_numerical': 0.0, 'mean_word_length': 5.1678321678321675, '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}}
Social Network Big Data Mining Method based on MapReduce

Online social network has gradually become an important medium for People's Daily communication and information sharing. Internet users can discuss hot news events, share pictures of daily life, comment on movies, books, food and so on in different social networks anytime and anywhere. The massive activity data left by a large number of Internet users in the social network is the online projection of users' real social relations, which contains huge data mining value. The characteristics of settlements similar to the real society are ubiquitous in social networks, and a large number of relational data with the characteristics of settlements can be defined by communities. Through the research of the potential information behind the community, we can dig out the transmission mode and change law of the information.