| Popis: |
The social media with music content is currently growing very quickly, many interactions that occur are based on the same interest in content. The relationship occurs between users of the music platform based on the influence of the same interest in music that can be seen in the form of a network. This study uses the idea-based percolation method (PIB) to identify social groups based on the listener's musical genre, the Louvain method to identify group modularity, and the clique-percolation method to identify overlapping communities. The generated network includes a bipartite network that is formed when listeners are connected to a music group and a unipartite network that is formed when listeners connect with listeners who have the same musical taste. The results show that there is a network of groups based on the relationship of preferred music tastes, there are 13 communities that are formed based on the value of modularity and there are overlapping communities with 10 nodes forming a k-clique. Furthermore, the results represent that in a music network, the influence of music taste is always initiated by one user, then spreads to other users. |
