{'fraction_non_alphanumeric': 0.017356475300400534, 'fraction_numerical': 0.0, 'mean_word_length': 5.25, '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}}
Unobtrusive Social Network Data From Email

Abstract : Email provides a rich source of longitudinal social network data that can be used for applications ranging from command and control, to military intelligence, to basic social science research. This project reviews several methods available to extract email network data and compares them in terms of data quality and convenience of collection. In general, it is preferable to obtain email data directly from the central SMTP email server. In situations where this is not possible, alternative approaches presented here can be useful. These techniques for analyzing email data have been automated in the Organizational Risk Analyzer (ORA) software, which is freely available to DoD and academia.