Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis
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, na...
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| Format: | Article |
| Language: | English |
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Ikatan Ahli Informatika Indonesia
2021-08-01
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| Series: | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| Subjects: | |
| Online Access: | http://jurnal.iaii.or.id/index.php/RESTI/article/view/3160 |
| _version_ | 1797333933916946432 |
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| author | Aprillian Kartino M. Khairul Anam Rahmaddeni Junadhi |
| author_facet | Aprillian Kartino M. Khairul Anam Rahmaddeni Junadhi |
| author_sort | Aprillian Kartino |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-08T08:13:18Z |
| format | Article |
| id | doaj.art-39fe07d40e4d4b9895811901212756dd |
| institution | Directory Open Access Journal |
| issn | 2580-0760 |
| language | English |
| last_indexed | 2024-03-08T08:13:18Z |
| publishDate | 2021-08-01 |
| publisher | Ikatan Ahli Informatika Indonesia |
| record_format | Article |
| series | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| spelling | doaj.art-39fe07d40e4d4b9895811901212756dd2024-02-02T08:05:31ZengIkatan Ahli Informatika IndonesiaJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)2580-07602021-08-015469770410.29207/resti.v5i4.31603160Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network AnalysisAprillian Kartino0M. Khairul Anam1Rahmaddeni2Junadhi3STMIK Amik RiauSTMIK Amik RiauSTMIK Amik RiauSTMIK Amik RiauCovid-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.http://jurnal.iaii.or.id/index.php/RESTI/article/view/3160centrality, covid-19, follower rank, social network analysis, twitter |
| spellingShingle | Aprillian Kartino M. Khairul Anam Rahmaddeni Junadhi Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) centrality, covid-19, follower rank, social network analysis, twitter |
| title | Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis |
| title_full | Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis |
| title_fullStr | Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis |
| title_full_unstemmed | Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis |
| title_short | Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis |
| title_sort | analisis akun twitter berpengaruh terkait covid 19 menggunakan social network analysis |
| topic | centrality, covid-19, follower rank, social network analysis, twitter |
| url | http://jurnal.iaii.or.id/index.php/RESTI/article/view/3160 |
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