{'fraction_non_alphanumeric': 0.009825327510917031, 'fraction_numerical': 0.0, 'mean_word_length': 4.916129032258064, '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}}
A Longitudinal Social Network Clustering Method Based on Tie Strength

Longitudinal social network clustering is an emerging research area with many applications. Previous research typically focuses on the development of the clusters in the longitudinal network. In this paper, we propose an alternative method for longitudinal social network clustering, in which we assume that the clustering and the evolution of the network are the results of its inner structure, the strength of the ties among the nodes in the network. We estimate the strength of the ties based on the evolution of the network over time through a continuous Markov process and then clustering the network based on the strength of the ties of the whole network. A simulation study shows that the proposed method performs well under a variety of conditions. The application of the method is illustrated through the analysis of a real set of data.