COMPLEX NETWORK ANALYSIS ON INSTAGRAM INFLUENCER COMMUNITIES USING A COMBINED METHOD OF GENETIC ALGORITHMS AND SIMULATED ANNEALING

• Main Author: Putri Meilynna, Ayundha
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/65135
• Institution: Institut Teknologi Bandung

Nowadays, physicists have become interested in implementing physics into the economic and social fields. On a broad scale, they view these fields as a complex system. Complex Systems consist of agents and interactions between them. This model can be represented in a graph or network. A graph is a structure of a group of nodes and edges connecting two nodes. A community in a network is a group of nodes that are highly connected to each other than to any other node in the network. The process of establishing and identifying communities in a network is called community detection. In this study, the method used is the Genetic Algorithm method which is optimized by the Simulated Annealing Algorithm to detect communities that can assist in analyzing social networks on the Instagram influencer network which is included in 44 Ultimate list of Instagram influencers in Indonesia. The results obtained for the use of a combination of Genetic Algorithm and Simulated Annealing on Instagram influencer network are detecting 4 communities with a modularity value of 0,65.