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Song Theme Classification Dataset
Entertainment & Media Consumption
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Free
About
This dataset is curated for the purpose of classifying lyrical themes, providing a collection of song lyric excerpts each assigned to one of two distinct categories. It serves as a valuable resource for developing and evaluating machine learning models aimed at text classification, particularly within the realm of music analysis. The dataset facilitates tasks such as understanding content and categorising lyrical expressions.
Columns
- lyric: This column contains individual lines or short phrases extracted from song lyrics.
- class: This is a binary classification column, where each entry is either '0' or '1'. This numerical value represents the assigned theme or category for the corresponding lyric. For instance, in some applications, '1' may denote Pop genre lyrics, whilst '0' signifies Rap genre lyrics, or it could represent other specific lyrical themes.
Distribution
The data file is typically supplied in a CSV format. Whilst specific numbers for records are not provided, the dataset is structured with two clear columns: 'lyric' and 'class'. A sample file is intended to be uploaded to the platform separately for examination.
Usage
This dataset is highly suitable for various applications and use cases, including:
- Developing and refining Natural Language Processing (NLP) models for text understanding.
- Building and testing text classification systems focused on musical lyrics.
- Training machine learning algorithms for automatic prediction of lyrical themes or music genres.
- Facilitating research in computational musicology, exploring patterns and sentiments within song content.
Coverage
The dataset has a global scope, concentrating solely on lyrical content. Details regarding specific time ranges, geographic origins of the lyrics, or demographic information of the artists or audience are not explicitly covered within the dataset's parameters.
License
CC0 License
Who Can Use It
- Data Scientists and Machine Learning Engineers: Ideal for those creating and validating text classification and NLP models.
- Researchers: Beneficial for individuals in academic or research settings focused on computational linguistics, music information retrieval, or broader NLP studies.
- Developers: Suitable for those building applications requiring the categorisation or analysis of textual song content.
- Academics: Useful for studies into the characteristics and prevalent themes found within popular music.
Dataset Name Suggestions
- Lyrical Theme Classifier Data
- Music Lyric Binary Categories
- Song Theme Classification Dataset
- Lyric Class Analysis
- Binary Lyrical Content
Attributes
Original Data Source: Music Genre Classification
QUALITY