SOCIAL NETWORK ANALYSIS DALAM PENGGUNAAN TAGAR #BOYCOTT SEBAGAI DAMPAK KONFLIK

Muhammad Fachrul  Salam; Namirah Khairunnisa; Kiky Resky Ramadhani  Sucipto

doi:10.32663/hwm58750

Authors

Muhammad Fachrul Salam Institut Teknologi dan Bisnis Kalla
Namirah Khairunnisa Institut Teknologi dan Bisnis Kalla
Kiky Resky Ramadhani Sucipto Institut Teknologi dan Bisnis Kalla

DOI:

https://doi.org/10.32663/hwm58750

Keywords:

Social Network Analysis, Twitter API, Cancel Culture, Centrality Metrics, Modularity and Density Metrics

Abstract

This study analyzes the #BoycottMcDonalds hashtag network on Twitter social media using Social Network Analysis (SNA) method to identify influential actors and the level of interaction that occurs in the network using centrality, density, and modularity metrics. Of the 2,468 tweets obtained through crawling Twitter data using the Twitter API, after the data preparation stage (pre-processing) there are only 810 tweets that are ready to be analyzed in Gephi. Determining influential actors in the #BoycottMcDonalds hashtag network is calculated using centrality metrics, namely degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality. The analysis results show that the irishpopeye account occupies the highest position in out-degree with a weight of 43 and in closeness centrality with a weight of 1.0. The second influental account is the mcdonalds account with the highest eigenvector centrality weight of 1.0 and the third influential account is the drloupis account with a fairly high eigenvector centrality and degree centrality value. As for the level of the interaction that occurs in the network, based on the modularity metric value obtained of 0.934 and density of 0.001 which indicates that the level of interaction in the #BoycottMcDonalds network is low.

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