Group Members:
- Uğur Sezer Aşıkoğlu
- Melisa Yılmaz
- Kalender Gülbudak
Exploratory Data Analysis:
- Visualizations descriptive statistics of the dataset; visual explanations of features & sharing distributions,
- Example visualizations of aggregated forms based on features (One example can be grouping the dataset based on genres and comparing distributions or centrality metrics of features for different genres),
- Analysis of the most popular artists and songs.
- Analyzing how songs of different genres change with time (Temporal analysis of features)
Statistical Analysis & Hypothesis Testing:
- Statistical tests to check how (or if) features contribute to popularity of songs
- Statistical tests to check if significant differences exist between different eras (like comparing features of 80s and 90s hip-hop)
Machine Learning:
- Prediction of song popularity with various machine learning models
- Efforts on hyper-parameter tuning to increase the performance of models
- Creating a simple song recommendation system using similarity metrics and Nearest Neighbors methods