Between 2000 and 2020—bracketing China's WTO-era opening and ending before the post‑pandemic disruption—Mandopop's circulation shifted from a label/broadcast economy toward digital platforms where visibility is increasingly mediated by streams, clicks, and content governance. I assert 2009, 2012, and 2018 as candidate inflection years (attention metricization; platform and licensing consolidation; and a later phase of mature infrastructure with stronger compliance pressures) and ask whether lyrical meaning changes in ways that align with these shifts. Mandopop lyrics are frequently discussed in terms of affect and gendered address, yet rarely analyzed at scale with reproducible computational methods. Thisstudy presents an ongoing NLP study of Mandopop lyrics released between 2000 and 2020, asking: (1) Do mainstream lyrics exhibit increasing semantic homogenization over time? (2) Are lyrical themes and sentiments systematically associated with performer gender (male vs. female solo singers), and do those differences converge or diverge across the period?

The corpus will comprise approximately 1,000–1,500 charting Mandarin-language tracks sampled annually from widely circulated year-end rankings and streaming-platform charts. To keep the gender comparison interpretable, the primary analysis focuses on solo artists with stable binary gender metadata; groups and ambiguous cases are reserved for robustness checks. Lyrics are collected from licensed APIs or public lyric databases and normalized (script harmonization, removal of paratext such as stage directions, and deduplication of re-releases).

For semantic representation, we use transformer encoders s (Devlin et al., 2019; Cui et al., 2020); long lyrics are segmented to fit context limits and then aggregated into song-level embeddings. Two complementary analyses follow. First, an embedding-based topic model (BERTopic) induces an interpretable theme inventory (Grootendorst, 2022). Topic prevalence trajectories (by year and gender) and within-year topic entropy provide operational measures of thematic concentration/diversity. Second, we estimate lyrical affect by fine-tuning a Chinese transformer on a stratified, human-annotated in-domain subset (n ~= 300; balanced by decade and gender) into coarse valence categories, building on evidence that lyrics alone can capture mood/valence information in Mandarin pop Chu et al., 2010). Annotation is performed blind to year and performer gender; inter-annotator reliability (Krippendorff's alpha) and systematic error analyses are reported.

Trend inference uses mixed-effects regression with random intercepts for artists (controlling repeated-author style) and sensitivity analyses under alternative sampling schemes. The study will report: (i) an empirically grounded map of major lyrical themes in Mandopop 2000–2020, (ii) longitudinal trajectories of semantic diversity and sentiment, and (iii) gender-stratified comparisons that explicitly address stereotype-bearing lexical fields and potential model bias (Betti et al., 2023).