Upbeat and Quirky, With a Bit of a Build: Communicating Meaning and Meeting Information Needs in the Music Industry

Music is widely used to accompany moving images, in films, advertising, television programmes and computer games. The process of choosing and using a piece of pre-existing commercial music for this purpose is known as synchronisation. The addition of music to a piece of film enhances the final work with cultural meaning, and generates additional income for the rights holders. This research examines the information needs of professionals involved in the selection of music, including Users from the advertising and film communities and Owners from the recording and publishing industries. A tentative communications model is developed and proposed from musicological, semiotic and communications literature. Interviews, knowledge organisation systems, queries and observations are identified as rich potential sources of textual data relating to the communications process around satisfying the Users’ information needs. The content of these texts is analysed to identify key musical facets. Mood is found to be an important factor when searching for unknown musical items. Using a Discourse Analytic approach to the interview texts, four discourses, or interpretive repertoires, are identified. These repertoires carry conflicting meanings of music and are employed throughout the community, although relative emphases vary according to the viewpoint of the stakeholder. This is supported by an analysis of the written texts of both the Owners (music search engines) and the Users (written queries, or briefs). A comparison is drawn between the emphasis of the repertoires and the precision of the search engines. The repertoires are applied to the theoretical communications model, which is revised to reflect the findings of the analyses. This is used to make recommendations on how to improve the disintermediated communications process, by emphasising the repertoires employed by the Users rather than those of the Owners

Music Dataset: Lyrics and Metadata from 1950 to 2019

This dataset was studied on Temporal Analysis and Visualisation of Music paper, in the following link: https://sol.sbc.org.br/index.php/eniac/article/view/12155 This dataset provides a list of lyrics from 1950 to 2019 describing music metadata as sadness, danceability, loudness, acousticness, etc. We also provide some informations as lyrics which can be used to natural language processing. The audio data was scraped using Echo Nest® API integrated engine with spotipy Python’s package. The spotipy API permits the user to search for specific genres, artists,songs, release date, etc. To obtain the lyrics we used the Lyrics Genius® API as baseURL for requesting data based on the song title and artist name