ANALISIS JARINGAN SOSIAL TWITTER TENTANG ISU KLITIH DI DAERAH ISTIMEWA YOGYAKARTA

Wibowo, Anshari Tri (2023) ANALISIS JARINGAN SOSIAL TWITTER TENTANG ISU KLITIH DI DAERAH ISTIMEWA YOGYAKARTA. Other thesis, UPN "Veteran" Yogyajarta.

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Abstract

ABSTRAK
Penelitian ini bertujuan menganalisis jaringan sosial Twitter terkait isu
"klitih" di Daerah Istimewa Yogyakarta menggunakan Metode Social Network
Analysis (SNA). Dengan rentang waktu 1 Januari 2022 hingga 30 Juni 2023,
penelitian ini mengumpulkan 749 percakapan menggunakan kata kunci "klitih".
Pengumpulan data dilakukan melalui text mining dan web scraping menggunakan
colab.research.google.com. Hasil analisis jaringan menunjukkan adanya 1404
nodes dan 748 edges, mengindikasikan kekuatan topik "klitih" dalam menciptakan
jaringan komunikasi yang besar. Terdapat tujuh aktor utama, dengan
@mizanzulaikha sebagai aktor terbesar. Cluster interaksi menunjukkan pola
terpecah tanpa membentuk jaringan komunikasi yang terhubung
sepenuhnya.Properti analisis jaringan mencakup Average Degree (0.533), Density
(0.000), Diameter (1), dan Average Path Length (1.0). Sentimen positif mencapai
5.40541, sedangkan sentimen negatif -6.06061, menunjukkan variasi yang
signifikan antara keduanya. Word cloud menyoroti kata kunci utama seperti 'jogja',
'orang', dan 'klitih'. Kesimpulan menunjukkan kompleksitas jaringan komunikasi
terkait isu "klitih" di Twitter. Dikarenakan Penelitian ini memunculkan jaringan
yang cukup luas, namun aktor yang dihasilkan tidak saling terhubung serta
pemahaman mendalam mengenai struktur, aktor terlibat, dan sentimen dalam
percakapan "klitih" di Daerah Istimewa Yogyakarta.
Kata kunci : Klitih, DIY, Twitter, Social Network Analysis(SNA), Sentiment
Analysis.
ABSTRACK
This research aims to analyze the Twitter social network related to the issue of "klitih"
in the Special Region of Yogyakarta using the Social Network Analysis (SNA) method. With a
time span of January 1, 2022 to June 30, 2023, this research collected 749 conversations using
the keyword "klitih". Data collection was carried out through text mining and web scraping
using colab.research.google.com. The network analysis results show that there are 1404 nodes
and 748 edges, indicating the power of the "klitih" topic in creating a large communication
network. There are seven main actors, with @mizanzulaikha as the biggest actor. Interaction
clusters show fragmented patterns without forming a fully connected communication network.
Network analysis properties include Average Degree (0.533), Density (0.000), Diameter (1),
and Average Path Length (1.0). Positive sentiment reached 5.40541, while negative sentiment
was -6.06061, indicating significant variation between the two. The word cloud highlights main
keywords such as 'jogja', 'people', and 'klitih'. The conclusion shows the complexity of the
communication network regarding the issue of "klitih" on Twitter. Because this research
produces a fairly extensive network, the resulting actors are not connected to each other and
there is no deep understanding of the structure, actors involved, and sentiments in "klitih"
conversations in the Special Region of Yogyakarta.
Key Words : Klitih, DIY, Twitter, Social Network Analysis(SNA), Sentiment Analysis.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Klitih, DIY, Twitter, Social Network Analysis(SNA), Sentiment Analysis.
Subjects:	H Social Sciences > H Social Sciences (General)
Divisions:	Faculty of Law, Arts and Social Sciences > School of Social Sciences
Depositing User:	Eko Yuli
Date Deposited:	20 Dec 2023 02:53
Last Modified:	20 Dec 2023 02:53
URI:	http://eprints.upnyk.ac.id/id/eprint/38371

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