An Analytical Methodology for the Investigation of the Relationship of Music and Lyrics in Popular Music

This thesis details the conception and design of a new methodology for examining pop songs holistically; considering both music and lyrics and examining the synergies between the two. Central to this methodology is the application of a data extraction framework, which has been designed to mine information about musical and lyrical phenomena. This framework operates as a common source for producing data about two very different media, avoiding individual interpretation where this is possible. The methodology has been designed to address specific questions about the relationship between music and lyrics, but the main purpose of the thesis is to evaluate the usefulness of the endeavour. In order to examine the efficacy of this approach, the framework was used to populate a dataset made up of a sample of 300 songs, which was subsequently explored and analysed through a series of case studies which investigate combinations of metrics concerned with music and lyrics for the whole sample, as well as analysis of specific subsets defined by a range of parameters. These case studies have demonstrated the various ways this approach might be used, as well as working as proof of concept. The conclusion of the thesis reviews the various case studies in the context of presenting potential uses of the framework as a tool and the broader methodology by other scholars. There is also a consideration of how the overall data might be affected by the inclusion of genres and styles that are not included in the initial sample set