To develop a machine learning model for detecting fake product reviews in the education sector.
To analyze the impact of fake reviews on students, educators, and educational institutions.
To propose methods for improving the authenticity and credibility of product reviews in the education industry.
Collect and preprocess a dataset of product reviews in the education sector.
Implement machine learning algorithms for fake review detection, such as sentiment analysis and natural language processing.
Evaluate the performance of the model using metrics like accuracy, precision, recall, and F1-score.
Conduct a comparative analysis with existing fake review detection techniques in other industries.
Prepare a research report documenting the methodology, results, and recommendations for future research in the field of fake product review detection in education.
