SIT717 Enterprise Business Intelligence: Health Tweets Analysis Report

This technical report analyzes a dataset of health response tweets using data mining and machine learning techniques within the WEKA environment. The report begins with an executive summary and an introduction that explains the background of the study, focusing on how machine learning improves health and business relations. It then details data preprocessing steps, including converting text files to CSV format and cleaning the data. The report summarizes the dataset, highlighting key variables like tweet IDs and URLs. Data mining techniques, specifically clustering and classification, are discussed, with a focus on classification using decision trees and Naive Bayes algorithms. The report also includes data exploration visualizations and detailed explanations of the machine learning models. The report covers the application of machine learning algorithms and discusses the results of the analysis and performance evaluation. This comprehensive report is a contribution to Desklib, providing students with valuable insights into data analysis and machine learning applications.