Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social
Network Analysis
Dublin Core
Title
Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social
Network Analysis
Network Analysis
Subject
Centrality, Covid-19, Follower Rank, Social Network Analysis, Twitter
Description
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 academic.droneemprit.id 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.
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 academic.droneemprit.id 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.
Creator
Aprillian Kartino1
, M. Khairul Anam2
, Rahmaddeni3
, Junadhi4
, M. Khairul Anam2
, Rahmaddeni3
, Junadhi4
Publisher
STMIK Amik Riau
Date
20-08-2021
Contributor
Fajar bagus W
Format
PDF
Language
Indonesia
Type
Text
Files
Collection
Citation
Aprillian Kartino1
, M. Khairul Anam2
, Rahmaddeni3
, Junadhi4, “Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social
Network Analysis,” Repository Horizon University Indonesia, accessed May 23, 2025, https://repository.horizon.ac.id/items/show/8897.
Network Analysis,” Repository Horizon University Indonesia, accessed May 23, 2025, https://repository.horizon.ac.id/items/show/8897.