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Analyzing Artist Emergence and Influence Through Knowledge Graphs and Predictive Visual Analytics

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorChatzimparmpas, A.
dc.contributor.authorGezgin, Ceyda
dc.date.accessioned2025-08-28T00:03:39Z
dc.date.available2025-08-28T00:03:39Z
dc.date.issued2025
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/50071
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectThis thesis explores the 2025 VAST Challenge Mini-Challenge 1 by applying visual analytics techniques to a large-scale music knowledge graph. It analyzes artist Sailor Shift’s career, the evolution of the Oceanus Folk genre, and identifies potential emerging artists through interactive visualizations and predictive tools.
dc.titleAnalyzing Artist Emergence and Influence Through Knowledge Graphs and Predictive Visual Analytics
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuApplied Data Science
dc.thesis.id52705


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