Zulfikar, Wildan Budiawan and Wahana, Agung and Wildiansyah, Wildan Najah and Atmadja, Aldy Rialdy and Ramdania, Diena Rauda and Subaeki, Beki (2021) A deep learning approach to analyze the sentiment of online game users. In: ICWT 2021. (Unpublished)
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Abstract
The policies to be set by online game developers can depend on user sentiment. This study aims to obtain information about the sentiment of online game users as one of the bases for decision making. The Convolutional Neural Network (CNN) algorithm is a method of deep learning that is used to obtain classification results regarding game user sentiment. The methodology used is the Cross-Industry Standard Process for Data Mining. Then preprocessing and weighting was carried out using GloVe. The accuracy value of the CNN algorithm is 81%. And it shows 80.4% is positive and 19.6% is negative. The results of this study can be used to assist in decision-making, which is then seen from the opinions of game players.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | deep learning; CNN; convolutional neural network; social media; dota |
| Subjects: | Data Processing, Computer Science |
| Divisions: | Fakultas Sains dan Teknologi > Program Studi Teknik Informatika |
| Depositing User: | Wildan Budiawan Zulfikar |
| Date Deposited: | 02 May 2023 02:39 |
| Last Modified: | 02 May 2023 03:21 |
| URI: | https://etheses.uinsgd.ac.id/id/eprint/67089 |
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A Deep Learning Approach To Analyze The Sentiment Of Online Game Users. (deposited UNSPECIFIED)
- A deep learning approach to analyze the sentiment of online game users. (deposited 02 May 2023 02:39) [Currently Displayed]
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