Rap music is one of the biggest music genres in the
world today. Since the early days of rap music, references not only
to pop culture but also to other rap artists have been an integral
part of the lyrics’ artistry. Rappers may use them to introduce
their shared personal backgrounds such as where they grew up.
In addition, rap musicians reference each other by adopting
fragments of lyrics, for example, to give credit. This kind of text
reuse can be used to create connections between individual artists.
Due to the large amount of lyrics, only automated detection
methods can efficiently detect text reuse. In addition, automated
methods can also be used to identify similar artists based on
their lyrical content. Here, we present a visualization system for
analyzing text reuse in rap music lyrics. The system supports
the user of detecting text reuse and allusions between songs
and exploring connections between artists. For this purpose, we
crawled song lyrics and their metadata of selected American
rap artists from Genius.com. We also trained a network tailored
specifically for rap lyrics, which we named “rapBERTa”, to
compute similarities in lyrics.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:79826 |
| Date | 07 July 2022 |
| Creators | Meinecke, Christofer, Schebera, Jeremias, Eschrich, Jakob, Wiegreffe, Daniel |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | urn:nbn:de:bsz:15-qucosa2-798165, qucosa:79816 |
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