@conference {906,
	title = {Detecting Text Reuse and Similarities between Artists in Rap Music through Visualization},
	booktitle = {LEVIA{\textquoteright}20: Leipzig Symposium on Visualization in Applications 2020},
	year = {2020},
	address = {Leipzig},
	abstract = {Detecting references and similarities in music lyrics
can be a difficult task. Crowdsourced knowledge platforms like
Genius can help in this process through user annotated
information about the artist and the song but fail to include
visualizations to help users finding similarities and structures on
a higher and more abstract level. We propose a prototype to
detect and visualize the similarity of rap artists based on their
lyrics and monolingual alignments of song lyrics. For this, we
apply word and sentence embeddings to lyrics we crawled from
Genius.},
	keywords = {Intertextuality, Text Reuse, Visualization},
	doi = {10.31219/osf.io/j4cn8},
	url = {https://osf.io/j4cn8/},
	author = {Meinecke, Christofer and J{\"a}nicke, Stefan}
}
@conference {887,
	title = {Automated Alignment of Medieval Text Versions based on Word Embeddings},
	booktitle = {LEVIA{\textquoteright}19: Leipzig Symposium on Visualization in Applications 2019},
	year = {2019},
	address = {Leipzig},
	abstract = {Medieval textuality is characterized by instability in text structure and length that varies according to the text tradition. This instability in the versions, otherwise known as {\textquotedblleft}mouvance{\textquotedblright}, is characterized by dialectal difference, traces of orality, the modification of wording and even the rewriting and rearrangement of large parts of the text. To help humanities scholars in the exploratory analysis of such complex text collections, the visual analytic system iteal was initially proposed. The system aligns similar phrases on a line-level on the basis of string similarity and word n-grams. We propose an extension of this system that replaces the parameter-based approach with an automatic one using word embeddings thereby adding a semantic component. The benefit of the new visualization system is shown through a comparison of different versions of medieval French texts. Additionally, a domain-expert compared the parameter-based approach with the approach based on word embeddings to outline the similarities and differences in the alignments.},
	keywords = {Digital Humanities, Sentence Alignment, Visualization, Word Embedding},
	doi = {10.31219/osf.io/tah3y},
	url = {https://levia19.vizcovery.de/papers/LEVIA19_paper_6.pdf},
	author = {Meinecke, Christofer and Wrisley, David Joseph and J{\"a}nicke, Stefan}
}
