The Framework for Political Communication Text Mining Based on Twitter
In recent years, social media as a medium that is widely used in communication in the community. The phenomenon of communication on social media is increasingly being used in political communication. Social networking site services like Twitter and Facebook are believed to have the potential to...
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my-aeu-eprints.8502021-03-31T01:26:22Z http://ur.aeu.edu.my/850/ The Framework for Political Communication Text Mining Based on Twitter Jufri, . Aedah, Abd Rahman Suarga, . In recent years, social media as a medium that is widely used in communication in the community. The phenomenon of communication on social media is increasingly being used in political communication. Social networking site services like Twitter and Facebook are believed to have the potential to increase public participation in politics. Twitter is an ideal platform for voters, politicians, political parties, and political institutions to disseminate not only public information but also political opinions to the public through their networks. This research is related to the effectiveness of social media (Twitter) as a means of political communication used by the public, especially in the election of the Mayor of Makassar and other elections in Indonesia. This paper, using two methods for social media analysis on political communication. Support Vector Machine (SVM) to classify predictable words or sentences, and the K-Means method is used to classify words or sentences related to political communication. The results of this study can be used by voters, candidates, political parties, and political institutions, as information and also as a measurement aid in determining the choice of candidates. 2020 Conference or Workshop Item PeerReviewed text en http://ur.aeu.edu.my/850/1/09320805.pdf Jufri, . and Aedah, Abd Rahman and Suarga, . (2020) The Framework for Political Communication Text Mining Based on Twitter. In: 2nd International Conference on Cybernetics and Intelligent System, 27 - 28 October 2020, Manado, Indonesia. |
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In recent years, social media as a medium that is
widely used in communication in the community. The
phenomenon of communication on social media is increasingly being used in political communication. Social networking site services like Twitter and Facebook are believed to have the potential to increase public participation in politics. Twitter is an ideal platform for voters, politicians, political parties, and
political institutions to disseminate not only public information but also political opinions to the public through their networks. This research is related to the effectiveness of social media (Twitter) as a means of political communication used by the public, especially in the election of the Mayor of Makassar and other elections in Indonesia. This paper, using two methods for social media analysis on political communication. Support
Vector Machine (SVM) to classify predictable words or
sentences, and the K-Means method is used to classify words or sentences related to political communication. The results of this study can be used by voters, candidates, political parties, and political institutions, as information and also as a measurement
aid in determining the choice of candidates. |
format |
Conference or Workshop Item |
author |
Jufri, . Aedah, Abd Rahman Suarga, . |
spellingShingle |
Jufri, . Aedah, Abd Rahman Suarga, . The Framework for Political Communication Text Mining Based on Twitter |
author_facet |
Jufri, . Aedah, Abd Rahman Suarga, . |
author_sort |
Jufri, . |
title |
The Framework for Political Communication Text Mining Based on Twitter |
title_short |
The Framework for Political Communication Text Mining Based on Twitter |
title_full |
The Framework for Political Communication Text Mining Based on Twitter |
title_fullStr |
The Framework for Political Communication Text Mining Based on Twitter |
title_full_unstemmed |
The Framework for Political Communication Text Mining Based on Twitter |
title_sort |
framework for political communication text mining based on twitter |
publishDate |
2020 |
url |
http://ur.aeu.edu.my/850/1/09320805.pdf http://ur.aeu.edu.my/850/ |
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1696979749275959296 |
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