# "More Than Words": Linking Music Preferences and Moral Values Through Lyrics

arXiv: https://arxiv.org/abs/2209.01169 · HTML: https://mlsanity.com/paper/2209.01169/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 61 references that are in the map.
- First posted on arXiv 2 Sep 2022.

## Builds on (most cited first, 12 of 12)

- [A Unified Approach to Interpreting Model Predictions](https://mlsanity.com/paper/1705.07874/) (2017)
- [ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing](https://mlsanity.com/paper/1902.07669/) (2019)
- [Crowdsourcing a Word-Emotion Association Lexicon](https://mlsanity.com/paper/1308.6297/) (2013)
- [MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations Prediction](https://mlsanity.com/paper/1904.08314/) (2019)
- [Acquiring Background Knowledge to Improve Moral Value Prediction](https://mlsanity.com/paper/1709.05467/) (2017)
- [Predicting Demographics, Moral Foundations, and Human Values from Digital Behaviors](https://mlsanity.com/paper/1712.01930/) (2017)
- [A high-reproducibility and high-accuracy method for automated topic classification](https://mlsanity.com/paper/1402.0422/) (2014)
- [Human Values and Attitudes towards Vaccination in Social Media](https://mlsanity.com/paper/1904.00691/) (2019)
- [Modelling Moral Traits with Music Listening Preferences and Demographics](https://mlsanity.com/paper/2107.00349/) (2021)
- [Effect of Values and Technology Use on Exercise: Implications for Personalized Behavior Change Interventions](https://mlsanity.com/paper/1903.11579/) (2019)
- [Young Adult Unemployment Through the Lens of Social Media: Italy as a case study](https://mlsanity.com/paper/2010.04496/) (2020)
- [How Much do Lyrics Matter? Analysing Lyrical Simplicity Preferences for Individuals At Risk of Depression](https://mlsanity.com/paper/2109.07227/) (2021)

## Built on by (most cited first, 2 of 2)

- [Search Engine and Recommendation System for the Music Industry built with JinaAI](https://mlsanity.com/paper/2308.03842/) (2023)
- [Towards Estimating Personal Values in Song Lyrics](https://mlsanity.com/paper/2408.12694/) (2024)

## Abstract (arXiv)

This study explores the association between music preferences and moral values by applying text analysis techniques to lyrics. Harvesting data from a Facebook-hosted application, we align psychometric scores of 1,386 users to lyrics from the top 5 songs of their preferred music artists as emerged from Facebook Page Likes. We extract a set of lyrical features related to each song's overarching narrative, moral valence, sentiment, and emotion. A machine learning framework was designed to exploit regression approaches and evaluate the predictive power of lyrical features for inferring moral values. Results suggest that lyrics from top songs of artists people like inform their morality. Virtues of hierarchy and tradition achieve higher prediction scores (.20 ≤ r ≤ .30) than values of empathy and equality (.08 ≤ r ≤ .11), while basic demographic variables only account for a small part in the models' explainability. This shows the importance of music listening behaviours, as assessed via lyrical preferences, alone in capturing moral values. We discuss the technological and musicological implications and possible future improvements.