Sentiment Analysis of Genshin Impact on Twitter Using Naïve Bayes
Abstract
Abstract—During the COVID-19 pandemic that interferes
normal life around the world, people have an obligation to stay at
home and quarantine themselves. This has led to an increase in
the consumption of entertainment, especially online gaming which
is known to be less harmful than other stress and aversive
emotions. And Genshin Impact is one of the online games that won
Google Play's the Best Game of 2020 award when pandemic
happening. Released in September 2020 by China video game
developer, miHoYo. Co., Ltd, Genshin Impact has been a hot
trend on the microblogging platform, Twitter. The purpose of this
research is to provide information regarding people's opinion
emotion in their tweets toward Genshin Impact and this
information will be a helpful resource for game improvement and
can be used as reference of future research. By using sentiment
analysis to help analyze the emotion contained in the text, the
result will be categorized into three categories: positive, negative,
or neutral sentiment. The data is gained through text mining then
will be processed as text classified using Naive Bayes algorithm.
Thus, the model will be going through evaluation of model's
performance to measure how accuracy it is. The result of it stated
that the best ratio between training and test set is 60:40 with
71.80% test accuracy, yet the accuracy between 3 others ratio is
not much difference. That’s why using hyperparameter tuning
can find the optimal result. After finding the optimal result, the
highest result it can get is 72.14%. Besides that, people on Twitter
mostly perceive the game in neutral sentiment.
Keywords—Sentiment Analysis, Genshin Impact, Naïve Bayes Classifier
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