{'fraction_non_alphanumeric': 0.018271257905832748, 'fraction_numerical': 0.004919184820801124, 'mean_word_length': 4.983193277310924, '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': 3, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Using the interaction on social networks to predict real life friendship

In today's world, social networks are one of the most popular ways of communication. Communication and relations among people can be monitored based on interaction on social networks. The question is the exact meaning of this interaction and can the real life relationship be interpreted from interaction on social networks. In this study, we used the most popular social network Facebook with the aim of finding the correlation between the interaction among users on Facebook and friendship in real life. In this paper, we propose a model for calculating the weight of friendship among users of social networks based on their interactions on Facebook. The model takes into account the general significance of a particular form of interaction (like, comment, etc.) and the specific significance of this form of interaction for each user. Apart from creating a model for calculating the weight of friendship, in this paper, general significance ratio of each communication parameter was experimentally determined. The model was built and evaluated by searching intersection of two sets, a set of user's 10 best friends that he himself cited and a set of 10 best friends obtained using the proposed model. Average overlapping of these two sets was 70.9%. Additionally, the overlap level of these two sets for different demographic groups was analyzed.