This study examines sustainable dissemination of digital music on TikTok by linking musical‐aspect discourse and network positioning to engagement and recommendation performance, using 1200 TikTok songs/videos, each represented by 52 platform and interaction features. Using a hybrid CF + NCF recommender with time‐series forecasting, the predictive pipeline achieved F 1 = 0.7879, AUC = 0.8373, and root mean squared error (RMSE) = 0.2143, while the ensemble forecaster yielded the lowest MAE = 0.2338 and RMSE = 0.3287 relative to ARIMA and Prophet. Content‐side evidence showed that lyric‐related sentiment was most prominent (84.91% positive mentions), exceeding production (52.78%) and melody, and matching results similarly prioritized lyrics over other musical aspects (exact: 30 vs. 19 vs. 17 and fuzzy: 53 vs. 39 vs. 29). Network analysis identified 1177 users and 164,499 ties partitioned into four communities, with the most bridging actor in Community 0 reaching betweenness centrality of 0.021, indicating concentrated brokerage in dissemination pathways. Together, these results suggest that lyric‐centered engagement and community brokerage co‐occur with stronger predictive and recommendation performance, providing an empirical basis for designing more durable TikTok dissemination strategies for digital music.
na et al. (Thu,) studied this question.