Erwianta Gustial Radjah
Universitas Kristen Satya Wacana, Salatiga

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Analisis Terhadap Tagar #LGBT di Twitter Menggunakan Analisis Jaringan Sosial (SNA) Erwianta Gustial Radjah; Ade Iriani; Daniel H.F. Manongga
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5476

Abstract

Twitter is utilized to express opinions and respond to social phenomena in real life. Responses to events through Twitter conversations are relatively fast and create popular topics. Popular topics using hashtags are often used to attract, invite and influence other users to respond as well. In May 2022, the hashtag "#LGBT" was widely discussed, which was due to the invitation of a gay couple to attend a podcast by Youtuber Deddy Corbuzier. This resulted in a decrease in Deddy Corbuzier's subscribers and the blocking of one of the TikTok accounts of a gay couple. This study aims to analyze opinions on social media that influence the decisions of other social media users. Negative impacts on content creators and affects the real-life community of religious Indonesians. An analysis of network structure, group, and actors involved was conducted using Social Network Analysis to detect and study the opinions that occurred. Network structure mapping of Density, Diameter, and Reciprocity. Group detection using Modularity and Centrality to identify influential actors. Crawling Dataset of 10,000 tweets with 7,761 nodes (actors) and 8,371 edges. The results of the network structure research showed the farthest distance to reach other accounts is 18 (Diameter), the low-Density value is 0.000164 and the low Reciprocity value between accounts is 0.049480. The results of the research show that the value of the group formed is relatively high, 0.868000. Centrality identification shows @brn as the account with the most connections of 287 and @sop as the account with the highest intermediary among other accounts at 0.000303, and @aiy as the account with the closest distance to other nodes at 1.0. Based on the quality of the node to other nodes, @brn is the highest at 1.0