Explorative Visual Analysis of Rap Music

Abstract

Detecting references and similarities in music lyrics can be a difficult task. Crowdsourced knowledge platforms such as Genius. can help in this process through user-annotated information about the artist and the song but fail to include visualizations to help users find similarities and structures on a higher and more abstract level. We propose a prototype to compute similarities between rap artists based on word embedding of their lyrics crawled from Genius. Furthermore, the artists and their lyrics can be analyzed using an explorative visualization system applying multiple visualization methods to support domain-specific tasks.

Traveling with Albrecht Dürer - A Case Study for Uncertainty-Aware Biography Visualization

“…to search for, create, curate, analyze, and communicate) cultural data, and to go beyond text-based formats by also visualizing arts and humanities data in various constellations [4,5]. With regard to art-historical knowledge, the last decades have seen a multitude of initiatives to build large biography data collections-mostly on a national level [6], which store information on the most important life events of thousands of artists and enable new forms of prosopographical research [7] and allow new ways of visual access to them [8,9,10,11,12]. Regarding artworks and cultural artifacts, cultural information often accumulates in objectoriented archives-whether for individual artists or in bigger databases which aggregate large numbers of subcollections [13].…”

LRFAF : une exploration numérique du rap français depuis les années 1990

“…entreprise à but lucratif revendiquant une propriété intellectuelle sur les textes, Genius offre un accès aisé à ses données à travers son API à qui sait programmer. Celles-ci ont été utilisées dans de nombreux projets hors de France (par exemple : Meinecke, Hakimi, and Jänicke 2021 ;Baltazar and Västfjäll 2020 ;Kryva and Dilai 2019). Concernant le rap français, quelques chercheurs se constituent manifestement des corpus massifs Klimentová (2022), tout comme les blogueurs spécialisés (voir par exemple l'ambitieuse infographie de RapMinerz ( 2023)).…”