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All Journal Jurnal EECCIS
Fadhil Rahmat
Universitas Amikom
Engineering

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Naive Bayes Method to Analyze Sentiment Accuracy on YouTube Comments Aditiya Rahman; Fadhil Rahmat; Sumarni Adi
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.627

Abstract

The revolution on social media has attracted users to video sharing sites like YouTube. This site is the most popular social media site where people see, share and interact by commenting on videos. There are various types of videos shared by users such as songs, movie trailers, news, entertainment etc. Some time ago the most trending video was a video about World War III (WWIII / WW3). Analyzing comments from videos about WW3 gives viewers opinions about WW3. Study the sentiments expressed in this commentary whether WW3 gets positive or negative feedback. The machine learning algorithm, Naive Bayes, is used in comments to find out its sentiments. The test results of 1500 data produced 30.3% positive sentiment and 60.6% negative sentiment, with an accuracy of 78.17%.
Co-Authors Aditiya Rahman Sumarni Adi