{'fraction_non_alphanumeric': 0.024175824175824177, 'fraction_numerical': 0.0, 'mean_word_length': 5.239726027397261, '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}}
Classification of social media shares using sentiment analysis

The use of social media is increasing rapidly today. With this increase, there is a lot of meaningful and meaningless data in social media environments. Parallel to this data formation, new working areas have also been formed. Sentiment analysis is an important area of study for generating meaningful information from this large data set. The sentiment analysis study, objectively indicates whether a phrase is positive, neutral or negative. That is, it is the process of determining whether the content is positive, negative or neutral. In this study, the analysis of the shares belonging to a certain Twitter user was performed by sentiment analysis method. Bayes algorithm is used in the analysis phase. Moreover, classification of users' categorization (news, politics, culture) according to their content has been successfully accomplished.