Weka (Waikato Environment for Knowledge Analysis) is a popular suite of machine learning software written in Java, developed at the University of Waikato, New Zealand. It is an open-source library that provides a collection of machine-learning algorithms for data mining tasks. In this article, we will explore how to use the Weka library to analyze Facebook data to gain insights into user behavior and preferences. We will walk through a real-world use case and provide code examples to help you get started with Weka.
Use Case: Analyzing Facebook User Likes and Interests
In this use case, we will analyze a dataset containing information about Facebook users, their likes, and interests. Our goal is to identify patterns and trends in user behavior and preferences, which can be used for targeted advertising or improving user experience on the platform.