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@article{207455,
        author = {Ishita Das},
        title = {K-Pop Chart Re-Entry & Comeback Momentum Analytics Dashboard},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {3},
        pages = {921-937},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207455},
        abstract = {The rapid global growth of the K-Pop industry has transformed music consumption into a highly data-driven ecosystem, where chart performance, audience engagement, and comeback strategies play a crucial role in determining an artist's long-term success. While existing music analytics primarily focus on streaming statistics and peak chart positions, limited attention has been given to understanding chart re-entry patterns, comeback momentum, fandom engagement, and content characteristics that influence sustained popularity. This study presents an interactive K-Pop Chart Re-Entry and Comeback Momentum Analytics Dashboard designed to provide comprehensive insights into historical chart performance using data visualization and exploratory analytics. The proposed system utilizes Python-based data processing techniques with Pandas for data preprocessing and feature engineering, Plotly for interactive visualizations, and Streamlit for developing a responsive web-based analytics dashboard. The dataset was cleaned, transformed, and analyzed to derive meaningful indicators such as re-entry frequency, comeback momentum scores, popularity trends, release-type distribution, fandom engagement, and artist performance. Multiple interactive modules, including Market Overview, Re-Entry Intelligence, Comeback Momentum, Fandom Intelligence, Content Insights, and Recommendation Analytics, enable users to explore chart behaviour through dynamic filtering and real-time visual exploration. The analysis reveals that several songs consistently re-enter music charts despite temporary declines, highlighting the impact of loyal fan communities, promotional activities, and release strategies on long-term chart sustainability. The dashboard further identifies relationships between album characteristics, explicit content, release formats, and popularity trends, providing actionable insights for music production companies, marketing teams, and entertainment analysts. By integrating interactive business intelligence with music analytics, the proposed system demonstrates an effective approach for monitoring chart dynamics and supporting data-driven decision-making within the rapidly evolving K-Pop industry.},
        keywords = {K-Pop Analytics, Music Intelligence, Data Visualization, Interactive Dashboard, Streamlit, Plotly, Python, Chart Re-Entry Analysis, Comeback Momentum, Business Intelligence, Exploratory Data Analysis},
        month = {August},
        }