Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis

Aprillian, Kartino and M. Khairul, Anam and Rahmaddeni, Rahmaddeni and Junadhi, Junadhi (2021) Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis. JURNAL RESTI (Rekayas a Sistem dan T eknol ogi Informasi ), 5 (4). pp. 697-704. ISSN 2580-0760

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Covid-19 is a disease of the virus that is shaking the world and has been designated by WHO as a pandemic. This case of
Covid-19 can be a place of dissemination of disinformation that can be utilized by some parties. The dissemination of
information in this day and age has turned to the internet, namely social media, Twitter is one of the social media that is often
used by Indonesians and the data can be analyzed. This study uses the social network analysis method, conducted to be able to
find nodes that affect the ongoing interaction in the interaction network of information dissemination related to Covid-19 in
Indonesia and see if the node is directly proportional to the value of its popularity. As well as to know in identifying the source
of Covid-19 information, whether dominated by competent Twitter accounts in their fields. The data examined 19,939 nodes
and 12,304 edges were taken from data provided by the web on the project "Analisis Opini
Persebaran Virus Corona di Media Sosial", using the period of December 2019 to December 2020 on social media Twitter.
The results showed that the @do_ra_dong account is an influential actor with the highest degree centrality of 860 and the
@detikcom account is the actor with the highest popularity value of follower rank of 0.994741605. Thus actors who have a
high degree of centrality value do not necessarily have a high follower rank value anyway. The study ignores if there are buzzer
accounts on Twitter.
Keywords: Centrality, Covid-19, Follower Rank, Social Network Analysis, Twitter

Item Type: Article
Subjects: H Social Sciences > H Social Sciences (General)
R Medicine > R Medicine (General)
T Technology > T Technology (General)
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Unnamed user with email
Date Deposited: 01 Dec 2021 08:16
Last Modified: 01 Dec 2021 08:16

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