• social
• network
• analysis
• computational
• intelligence
• k-means
• clustering
• nlp

Social networks are fundamental for studying the reactions of people worldwide to events of any kind: the launch of a new product by a company, the release of a teaser trailer for a film in production, and much more.
The speed with which ideas, videos, and images spread on the internet allows those who want to analyze the opinions and behaviors of groups of people, large or small, to easily retrieve the necessary data for research.
The objective of this thesis is to test and evaluate the effectiveness of a Java-Twitter application capable of detecting tweets in real-time related to a specific event and subsequently analyzing their content to extract data regarding the highlights, using the K-Means clustering algorithm from computational intelligence.