Building a Digital Twin of a Social Media User Based on Implicit Profile Data

This presents an algorithm for analyzing public open data gathered from social media. The problem of extracting information from Big Data collected from various social networks is considered. The article presents a new software solution to build a digital twin for a social media user based on implicit information, determined by substituted parameters. The algorithm is implemented in Python and uses social network API. The process of data collection, their pre-processing and filtering, as well as methods for analyzing the received data are described. The effectiveness of the algorithm is demonstrated on the example of data analysis from the popular social network VKontakte. The results obtained allow us to conclude that the proposed algorithm can be used to analyze and extract useful information from social media. The paper is oriented for engineers in the field of data analysis and social media. #COMESYSO1120.