We contribute a new dataset of English song lyrics, manually annotated with detailed information on the reasons for the explicitness (if any) of their content: Strong language; Substance abuse; Sexual reference; Reference to violence; Discriminatory language. The dataset consists of 4000 song lyrics, 1707 of them annotated as explicit and 2293 annotated as non-explicit by the human annotators. In details, the annotators tagged the explicit song lyrics as follows: 926 lyrics with Strong language; 266 lyrics with Substance abuse; 398 lyrics with Sexual reference; 771 lyrics with Reference to violence; and, 147 lyrics with Discriminatory language. The construction of the dataset is described in the following associated publication: Rospocher, M.; Eksir, S. Assessing Fine-Grained Explicitness of Song Lyrics. Information 2023, 14, 159. https://doi.org/10.3390/info14030159
Manually annotated song lyrics dataset with fine-grained explicitness information
Marco Rospocher
;Samaneh Eksir
2023-01-01
Abstract
We contribute a new dataset of English song lyrics, manually annotated with detailed information on the reasons for the explicitness (if any) of their content: Strong language; Substance abuse; Sexual reference; Reference to violence; Discriminatory language. The dataset consists of 4000 song lyrics, 1707 of them annotated as explicit and 2293 annotated as non-explicit by the human annotators. In details, the annotators tagged the explicit song lyrics as follows: 926 lyrics with Strong language; 266 lyrics with Substance abuse; 398 lyrics with Sexual reference; 771 lyrics with Reference to violence; and, 147 lyrics with Discriminatory language. The construction of the dataset is described in the following associated publication: Rospocher, M.; Eksir, S. Assessing Fine-Grained Explicitness of Song Lyrics. Information 2023, 14, 159. https://doi.org/10.3390/info14030159I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.