Abstract
Popular music lyrics are usually brief in length yet sophisticated in narrative content, emotional expression, and structural aesthetics. In this paper, we propose a graph-based analysis and interpretation framework for popular music lyrics using the sematic word embedding representation. This framework explores the temporal and structural information in music lyrics, such as word sequential pattern, lyric format pattern, and predominate song forms, to enhance the understanding of the interaction between the semantic and structural properties of music lyrics. Our proposed analysis and interpretation framework provides extensive tools for representing various properties of music lyrics as graph structural elements and then we implemented feature extraction tools for a comprehensive characterization of the lyric graph using graph analysis or complex network methodologies. The empirical studies based on contrasting music genres are then presented to illustrate the usage of the proposed tools and to demonstrate its modeling and analysis capabilities.
