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Social Network Monitoring and User Audience Analysis System

Student: Bukharov Sergey

Supervisor: Hadi Saleh

Faculty: Faculty of Computer Science

Educational Programme: System and Software Engineering (Master)

Final Grade: 7

Year of Graduation: 2020

Social networks are very important part of modern life. Nowadays, people use social networks every minute. They upload photos and videos, read posts, write posts, listen to music, look for job using social networks. A lot of people use social networks for driving they own business, they sell different goods, look for clients and estimate their competitors using social networks. Also, social networks contain enormous amount of user data, which can be analyzed and monitored. There are a lot of different tools for analyzing and monitoring of social networks, but all of them has the same big disadvantage - they were developed by marketers, analysts, somebody else, but not engineers. The most services don’t provides configurable and machine readable metrics and reports, so results aren’t analyzable. Analytics is usually weak or expensive. A lot of services work generally with only one social network. It sounds like reason to develop own system for social networks monitoring and analysis, using engineering approach. New system will allow to see real time metrics by social networks groups (e.g. likes, reposts, comments, etc.), all metrics will be configurable and machine readable. Also, it will identify users attributes (gender, age, city, relations, etc.). System will be based on Prometheus and Python. The system will be helpful for small businesses or startups, which can’t spent a lot of money for analytic tools, it will get opportunity to know a lot of details about their competitors.

Full text (added May 22, 2020)

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