<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Sentiment Analysis Genshin Impact Game to Know Players \r\nReaction and Expectation Using Support Vector Machine"^^ . "Sentiment Analysis Genshin Impact Game to Know Players \r\nReaction and Expectation Using Support Vector Machine\r\nArie Qur’ania1\r\n, Fajar Delli Wihartiko2\r\n, Muhammad Refansyach Sugianto3\r\n1Program Studi Ilmu Komputer, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas \r\nPakuan, Bogor, Jawa Barat, 16143, Indonesia\r\nAbstract\r\nAs the popularity of online games increases, it becomes important to know the sentiment of players \r\ntowards a particular game title. This study aims to determine the reactions and expectations of players in \r\ncommunity of game titled Genshin Impact, based on aspect of character, event and game as a whole in \r\ngame version 3.6. In this case, sentiment analysis is used to classify players opinion on YouTube comment \r\nand determine whether the opinion is positive, neutral or negative. The data used are player comments on \r\n6 YouTube videos uploaded by the official Genshin Impact Channel that promoting the new version of \r\nthe game, version 3.6. The process involved several steps like Scraping data comment, Cleaning, Case \r\nFolding, Tokenization, Filtering, Lemmatization, Feature Extraction using TF-IDF and Classification \r\nusing Support Vector Machine (SVM). The results showed that the overall sentiment of players towards \r\nversion 3.6 was positive. However, there are some player expectations and complaints that can be taken \r\ninto consideration by developers. In the character aspect, players expect the new characters, Kaveh and \r\nBaizhu, to have a stronger appeal. On the game aspect, players want long-term content to keep them \r\nmotivated to keep playing. On the event aspect, players complain that the events in this version seem very \r\nlong which makes players quickly get bored. The classification model with the SVM Algorithm \r\nsucceeded in providing a fairly high accuracy of 83% in the game and character aspects, while in the \r\nevent aspect the model provided a fairly good accuracy of 69%.\r\nKeywords: Sentiment Analysis; Genshin Impact; Version 3.6; expectations; SVM"^^ . "2023-02-06" . . . "Universitas Pakuan"^^ . . . "Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Pakuan"^^ . . . . . . . . . . . . . . . . . . "Arie"^^ . "Qur’ania"^^ . "Arie Qur’ania"^^ . . "Fajar"^^ . "Delli W"^^ . "Fajar Delli W"^^ . . "Muhammad Refansyach"^^ . "Sugianto"^^ . "Muhammad Refansyach Sugianto"^^ . . "Universitas Pakuan"^^ . . . "Fakultas Matematika dan Ilmu Pengetahuan Alam"^^ . . . "Program Studi Ilmu Komputer"^^ . . . . . . . "Sentiment Analysis Genshin Impact Game to Know Players \r\nReaction and Expectation Using Support Vector Machine (Text)"^^ . . . "Skripsi Refansyach 065119226.pdf"^^ . . "HTML Summary of #7677 \n\nSentiment Analysis Genshin Impact Game to Know Players \nReaction and Expectation Using Support Vector Machine\n\n" . "text/html" . . . "Ilmu Komputer"@en . .