Too Much Detail Kills the Vibe: Quantifying Lyrical Realism and Pop Music Virality

Pop music songwriters frequently deploy vivid real-world anchors, such as specific vehicle models and city names, to establish narrative realism. However, whether hyper-specific realism systematically drives commercial virality remains an unexamined empirical question. In this paper, we introduce an open-science computational framework that quantifies lyrical realism across 27 tracks from EDM-pop duo The Chainsmokers (2014-2024). By combining Brysbaert psycholinguistic concreteness norms (ILCA), named entity density, VADER sentiment analysis, and sentence embeddings with log-transformed YouTube view counts, we evaluate the structural drivers of pop virality. Statistical analysis reveals a negative rank correlation (Spearman r = -0.632, p < 0.001, 95% Confidence Interval [-0.814, -0.381]) and quadratic regression confirms a concave curvilinear relationship (quadratic beta = -2.18, p = 0.004), providing preliminary evidence consistent with a possible Inverted-U pattern. An estimated candidate optimal concreteness range (ILCA between 2.75 and 2.90) characterizes high-performing crossover tracks, whereas hyper-concreteness (ILCA greater than 3.20) marks a substantial reduction in streaming reach by over-saturating narrative details and restricting listener self-projection. Exploratory TreeSHAP attributions indicate that physical anchors must be balanced with chorus repetition and nostalgic sentiment to optimize streaming reach. All code, figure files, and datasets are open-sourced for computational reproducibility.