From peaks to people: The association between physical topography and generalized trust in China

Xu, Liang; Zeng, Shaoran; Jiang, Zehua; Sun, Zaoyi; Li, Hongting; Xu, Liuchang

doi:10.1016/j.jenvp.2023.102136

Journal of Environmental Psychology

2023

DOI: 10.1016/j.jenvp.2023.102136

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From peaks to people: The association between physical topography and generalized trust in China

Liang Xu,

Shaoran Zeng,

Zehua Jiang

et al.

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2024

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Cited by 3 publications

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Associations between lyric and musical depth in Chinese songs: Evidence from computational modeling

Xu,

Sun

et al. 2024

PsyCh Journal

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Musical depth, which encompasses the intellectual and emotional complexity of music, is a robust dimension that influences music preference. However, there remains a dearth of research exploring the relationship between lyrics and musical depth. This study addressed this gap by analyzing linguistic inquiry and word count‐based lyric features extracted from a comprehensive dataset of 2372 Chinese songs. Correlation analysis and machine learning techniques revealed compelling connections between musical depth and various lyric features, such as the usage frequency of emotion words, time words, and insight words. To further investigate these relationships, prediction models for musical depth were constructed using a combination of audio and lyric features as inputs. The results demonstrated that the random forest regressions (RFR) that integrated both audio and lyric features yielded superior prediction performance compared to those relying solely on lyric inputs. Notably, when assessing the feature importance to interpret the RFR models, it became evident that audio features played a decisive role in predicting musical depth. This finding highlights the paramount significance of melody over lyrics in effectively conveying the intricacies of musical depth.

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Associations between lyric and musical depth in Chinese songs: Evidence from computational modeling

Xu,

Sun

et al. 2024

PsyCh Journal

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Unveiling the Terrain of Fraud: Exploring the Association Between Physical Topography and Consumer Fraud Victimization

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Sun

et al. 2024

Deviant Behavior

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Psychological predictors of online fraud victimhood in China: a machine learning approach

Xu,

Wen,

Wang

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Psychology, Crime & Law

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From peaks to people: The association between physical topography and generalized trust in China

Cited by 3 publications

References 42 publications

Associations between lyric and musical depth in Chinese songs: Evidence from computational modeling

Associations between lyric and musical depth in Chinese songs: Evidence from computational modeling

Unveiling the Terrain of Fraud: Exploring the Association Between Physical Topography and Consumer Fraud Victimization

Psychological predictors of online fraud victimhood in China: a machine learning approach

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