Analysis of the use of artificial intelligence in social networks
Students Name: Tarnavskyi Oleh Yevhenovych
Qualification Level: magister
Speciality: Computer Control Systems for Moving Objects (Automobile Transport)
Institute: Institute of Computer Technologies, Automation and Metrology
Mode of Study: full
Academic Year: 2020-2021 н.р.
Language of Defence: ukrainian
Abstract: Tarnavsky O.E., Pavelchak A.G. (supervisor). Analysis of the use of artificial intelligence in social networks. Master’s thesis. - Lviv Polytechnic National University, Lviv, 2020. Extended abstract. Social networks use artificial intelligence to increase the efficiency of collecting and processing the information about social network users. Artificial intelligence [1] allows the networks to collect data via algorithms and use that information for monetization and advertising targeting within and outside the platform. One of the first algorithms for mass data collection were the Google search algorithms [2, 3]. Thanks to the updated method of information processing, the search algorithm began to find ways to improve the speed of processing results. The ability to decrease the search time appeared only because the possibility of identifying each user through the search history became real. Study object - social networks and analytical services. Scope of research - virtual private networks and connection protocols. Goal of research - to improve the service of private network user anonymization. Brief research results - a configuration of a virtual private network with increased speed was developed, which allows to anonymize the user when using search engines and social platforms. Keywords: social networks, indexing, search engines, Facebook, Google, targeting, SSL, VPN, certification, configuration. References. 1. Юлия Правик. Соцсети 2.0: Необходимость глобальной трансформации. - ЛитРес: Самиздат. - 2020. - 15-28 с. 2. Virginia Eubanks. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. - St Martin’s Press. - 2018. - 70-76 p. 3. Sarah T Roberts. Behind the Screen: Content Moderation in the Shadows of Social Media. - Yale University Press. - 2019. - 73 p. Tarnavsky O.E., Pavelchak A.G. (supervisor). Analysis of the use of artificial intelligence in social networks. Master’s thesis. - Lviv Polytechnic National University, Lviv, 2020. Extended abstract. Social networks use artificial intelligence to increase the efficiency of collecting and processing the information about social network users. Artificial intelligence [1] allows the networks to collect data via algorithms and use that information for monetization and advertising targeting within and outside the platform. One of the first algorithms for mass data collection were the Google search algorithms [2, 3]. Thanks to the updated method of information processing, the search algorithm began to find ways to improve the speed of processing results. The ability to decrease the search time appeared only because the possibility of identifying each user through the search history became real. Study object - social networks and analytical services. Scope of research - virtual private networks and connection protocols. Goal of research - to improve the service of private network user anonymization. Brief research results - a configuration of a virtual private network with increased speed was developed, which allows to anonymize the user when using search engines and social platforms. Keywords: social networks, indexing, search engines, Facebook, Google, targeting, SSL, VPN, certification, configuration. References. 1. Юлия Правик. Соцсети 2.0: Необходимость глобальной трансформации. - ЛитРес: Самиздат. - 2020. - 15-28 с. 2. Virginia Eubanks. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. - St Martin’s Press. - 2018. - 70-76 p. 3. Sarah T Roberts. Behind the Screen: Content Moderation in the Shadows of Social Media. - Yale University Press. - 2019. - 73 p.