Analisis Node dengan Centrality dan Follower Rank pada Twitter
Twitter is used to express about something that happened. In Indonesia since 2012, Twitter has been widely used for campaigns during regional or presidential elections. Apart from positive campaigns, negative campaigns and even black campaigns were carried out via Twitter, and tweets become twitwar....
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| Format: | Article |
| Language: | English |
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Ikatan Ahli Informatika Indonesia
2020-10-01
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| Series: | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
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| Online Access: | http://jurnal.iaii.or.id/index.php/RESTI/article/view/2398 |
| _version_ | 1797329373210083328 |
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| author | Evangs Mailoa |
| author_facet | Evangs Mailoa |
| author_sort | Evangs Mailoa |
| collection | DOAJ |
| description | Twitter is used to express about something that happened. In Indonesia since 2012, Twitter has been widely used for campaigns during regional or presidential elections. Apart from positive campaigns, negative campaigns and even black campaigns were carried out via Twitter, and tweets become twitwar. Twitter is a social network, so the data can be analyzed using a social network analysis approach. This research was conducted to analyze which nodes (actors) are influential using the degree, between, and closeness centrality methods, while the follower rank method is used for the analysis of popular actors in "# 4niesKingOfDrama". The data were 8895 nodes with 23257 edges taken from January 1 to February 20, 2020. The results showed that Degree Centrality was 212 with the actor who had the highest influence score was the account @ Bangsul__88 and actor @airin_nz was the actor with the highest popularity value with Follower Rank of 0.98211783. This study found that among the 10 main actors with the highest Degree Centrality values, there were several accounts that were buzzer accounts. The node (Actor) with the highest influence value is not necessarily the node with the highest popularity value. |
| first_indexed | 2024-03-08T07:04:44Z |
| format | Article |
| id | doaj.art-72a57d8728ae4a308e9904683bf5bbf9 |
| institution | Directory Open Access Journal |
| issn | 2580-0760 |
| language | English |
| last_indexed | 2024-03-08T07:04:44Z |
| publishDate | 2020-10-01 |
| publisher | Ikatan Ahli Informatika Indonesia |
| record_format | Article |
| series | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| spelling | doaj.art-72a57d8728ae4a308e9904683bf5bbf92024-02-03T04:59:26ZengIkatan Ahli Informatika IndonesiaJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)2580-07602020-10-014593794210.29207/resti.v4i5.23982398Analisis Node dengan Centrality dan Follower Rank pada TwitterEvangs Mailoa0UKSWTwitter is used to express about something that happened. In Indonesia since 2012, Twitter has been widely used for campaigns during regional or presidential elections. Apart from positive campaigns, negative campaigns and even black campaigns were carried out via Twitter, and tweets become twitwar. Twitter is a social network, so the data can be analyzed using a social network analysis approach. This research was conducted to analyze which nodes (actors) are influential using the degree, between, and closeness centrality methods, while the follower rank method is used for the analysis of popular actors in "# 4niesKingOfDrama". The data were 8895 nodes with 23257 edges taken from January 1 to February 20, 2020. The results showed that Degree Centrality was 212 with the actor who had the highest influence score was the account @ Bangsul__88 and actor @airin_nz was the actor with the highest popularity value with Follower Rank of 0.98211783. This study found that among the 10 main actors with the highest Degree Centrality values, there were several accounts that were buzzer accounts. The node (Actor) with the highest influence value is not necessarily the node with the highest popularity value.http://jurnal.iaii.or.id/index.php/RESTI/article/view/2398sna, degree centrality, betweness & closeness centrality, follower rank, twitter text mining |
| spellingShingle | Evangs Mailoa Analisis Node dengan Centrality dan Follower Rank pada Twitter Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) sna, degree centrality, betweness & closeness centrality, follower rank, twitter text mining |
| title | Analisis Node dengan Centrality dan Follower Rank pada Twitter |
| title_full | Analisis Node dengan Centrality dan Follower Rank pada Twitter |
| title_fullStr | Analisis Node dengan Centrality dan Follower Rank pada Twitter |
| title_full_unstemmed | Analisis Node dengan Centrality dan Follower Rank pada Twitter |
| title_short | Analisis Node dengan Centrality dan Follower Rank pada Twitter |
| title_sort | analisis node dengan centrality dan follower rank pada twitter |
| topic | sna, degree centrality, betweness & closeness centrality, follower rank, twitter text mining |
| url | http://jurnal.iaii.or.id/index.php/RESTI/article/view/2398 |
| work_keys_str_mv | AT evangsmailoa analisisnodedengancentralitydanfollowerrankpadatwitter |