Lois Mikael Camdesus, . (2023) ANALISIS SENTIMEN TERHADAP KONFLIK RUSIA-UKRAINA DI MEDIA SOSIAL TWITTER MENGGUNAKAN ALGORITMA NAÏVE BAYES. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Online social networks (OSNs) play an important role in sharing information in the event of a crisis. The sampel collected during such a crisis can largely reflect public opinion and sentiment. In addition, you can use OSN sample to investigate the different campaigns that different organizations use to influence public opinion, Such information sharing campaigns can range from factual dissemination to publicity and false alarms. Twitter is a platform for sharing media like a photo or video that makes it possible for users to taking photo and video, and sharing to many social network, including Twitter it self. Twitter it self have a mobile phone and website application, as time goes by, Twitter is not only using for a social media, but also used as a medium for telling argumentation about something. Analysis of Sentiment is a way to identify and classify the polarity of a given text at the level of phrases, sentences, and documents. Naive Bayes is one of classification method using probability and statistical methods proposed by a British Scientist named Thomas Bayes, which predict future probabilities based on past experience.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 1810511055] [Pembimbing: Ati Zaidiah] [Penguji 1: Jayanta] [Penguji 2: Henki Bayu Seta] |
| Uncontrolled Keywords: | Analysis of Sentiment, Twitter, Russia-Ukraine War, Naive Bayes Algorithm, Russo-Ukrainian Crisis, Russia, Ukraine, Conflict |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Lois Mikael Camdesus |
| Date Deposited: | 15 Aug 2023 02:44 |
| Last Modified: | 15 Aug 2023 02:44 |
| URI: | http://repository.upnvj.ac.id/id/eprint/25371 |
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