<![CDATA[The rapid growth of digital platforms has reshaped business strategies, with streaming services such as Netflix, Disney+, and Amazon Prime producing vast amounts of user and content data. This study investigates streaming content trends as a foundation for digital business strategy, emphasizing how genre analysis can guide short video promotion in 2026. The dataset originates from the Netflix Titles dataset on Kaggle, snapshot date March 2024, comprising 8,807 titles with 12 variables including release year, rating, duration, genre classification, and textual descriptions. Historical coverage spans 1925–2021, with the target variable defined as genre (listed_in). Class distribution is imbalanced, dominated by Comedy, Drama, and International Movies. Preprocessing involved imputation, categorical encoding, and TF-IDF vectorization to transform textual features into numerical form. Three analytical scenarios were applied. The first used the K-Nearest Neighbors (KNN) algorithm to classify genres, achieving 75.3% accuracy, 50.1% precision, 52.5% recall, and 44.8% F1-score, with confusion matrices revealing overlaps between Comedy and Drama. The second employed a Greedy Algorithm to heuristically select optimal content, prioritizing high ratings, recent release years, and shorter durations; top selections included The Silent Horizon (Sci-Fi & Fantasy, score 5.32), Family Bonds (Children & Family, score 4.21), and Comedy Nights (Comedy, score 5.10). The third scenario applied linear regression forecasting, yielding coefficients between 1.2–2.1, low forecast errors (RMSE 3.5–5.0, MAE 2.8–3.9), and predicted 2026 counts of 145 Comedy, 130 Action & Adventure, 120 Children & Family, 105 Romantic Drama, and 95 Sci-Fi & Fantasy titles, with uncertainty estimates reported at the 95% confidence level. Results confirm clustering around shorter durations and recurring themes such as family, love, survival, and discovery, reinforcing the suitability of short-form content for marketing. The integration of machine learning, heuristic selection, and forecasting demonstrates the potential of data-driven approaches to inform digital business strategies.]]>
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