User Interest Prediction based on Social Network Profile with Machine Learning

The explosion of social media data which holds important, massive, rapidly evolving unstructured information has provided an opportunity to research public opinion and know people's feelings. Capturing the views on social events, corporate strategies, political movements, marketing campaigns and product preferences et cetera brings growing interest from the scientific and business communities to improve their performances. This has resulted in an emerging field of social network mining or sentiment analysis. This paper describes a system that was built to analyze data from social media platforms such as Twitter, Instagram, Facebook and Reddit. The data is gathered from various services and programs which involves using the official API's and scraping tools. Machine Learning & Image Processing algorithms are applied on the gathered data to gain insights about the individual users' interests, usage patterns, media reachability, et cetera. These models are then relayed to a web application where various visualizations of the insights can be obtained.