Social Media Analysis with Machine Learning


Social networks have revolutionized the world. We all display personal information on social networks, thereby leaving a digital footprint on the Internet. The analysis of personal information can help companies conduct interviews, as it will give employers a full picture of a person, with a description of his/her personality and social behavior. Among the main problems of the analysis conducted there were the effective working groups formation and the allocation of deviant behavior based on the analysis of information from personal profiles on the social network VKontakte. In the course of this study, the data was collected, pre-processed, analyzed. After that users were organized into groups using machine learning and deep machine learning techniques. The analysis of data from users' social networks was carried out using neural networks and other machine learning methods, the K-means clustering algorithm being used for clustering users by interests.



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