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Semantic Homogenization in Italian Popular Music: A Diachronic Analysis

arXiv 2607.04832 ↗First posted 6 Jul 2026cs.CLcited by 0

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Abstract (arXiv)

In recent years, studies have revealed a decline in semantic variety across popular music lyrics, particularly in English-language songs on streaming platforms like Spotify. This research examines whether a similar trend can be observed in a different linguistic and cultural context: the lyrics of all finalist songs from the 75 editions of the Sanremo Music Festival, Italy's most renowned music competition. What sets this work apart is the development of a flexible and efficient methodology for tracking changes in semantic similarity over time, which can be applied to different datasets to study similar phenomena. Drawing on a combination of full-text, segment-based, topic-based, and word-level analyses, the approach leverages both embedding techniques and large language models. When applied to the Sanremo corpus, this framework reveals a gradual move toward increasing semantic uniformity, echoing the global patterns identified in previous studies. These findings underscore the value of natural language processing tools in uncovering long-term shifts in musical language and cultural expression.

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References · 8

  1. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  2. 2020ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERTcited by 1,160
  3. 2021ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interactioncited by 464
  4. 2024Multilingual E5 Text Embeddings: A Technical Reportcited by 357
  5. 2021AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processingcited by 131
  6. 2025MMTEB: Massive Multilingual Text Embedding Benchmarkcited by 120
  7. 2020On the Sentence Embeddings from Pre-trained Language Modelscited by 83
  8. 2024A Computational Analysis of Lyric Similarity Perceptioncited by 1

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