Beyond Melody: A Complex Network Framework for Cross-Cultural Music Plagiarism Analysis

Music can be considered a form of communicative expression that includes our feelings, identities, and social interactions. It crosses linguistic and cultural barriers. However, in the international music industry, plagiarism still poses a danger to morals, innovation, and legal compliance. In this work, we focus on the structural organization of the versional and plagiarized songs along with the original music tracks across five languages. We propose MUSiNET, a complex network architecture where nodes stand in for music tracks, and the significant value of the cosine similarity score is measured based on the intrinsic (audio) and extrinsic (metadata) features, determining the weighted edges connecting the nodes. We use the HITS algorithm to determine the threshold value of the edge weight to keep the significant edges in the proposed MUSiNET. The network displays the dynamics of the association between the original, plagiarized, and versioned songs using the curated dataset of 5000 tracks from the MUSICOSet dataset. The MUSiNET analysis reveals that plagiarized and versioned tracks frequently emerge as connectors that bridge genres, languages, and cultural boundaries. We observe that the composition of versional and plagiarized songs is not an isolated event in the music development community, but an integral relational process to achieve quick popularity based on the existing audience of the original composition.