Sentiment Analysis of Genshin Impact on X: Mental Health Implications Using TF-IDF and Support Vector Machine - Jaya, Sava Irhab Atma; Junta Zeniarja (Sinkron : jurnal dan penelitian teknik informatika, 2024)
Genshin Impact are now an integral part of daily life for many, potentially influencing mental well-being. Sentiment analysis window into these emotional effects, especially given the varied findings on gaming's impact on mental health. Analyzing X responses Genshin Impact using Support Vector Machine crucial, given its effectiveness in sentiment analysis. This study aims to deepen our understanding game's psychological impact and support development mental health interventions for gamers. The SVM classification report shows promising precision: 0.68 for Negative, 0.63 for Neutral, and 0.72 for Positive sentiment. However, recall rates favor Positive reviews (0.87) over Negative (0.56) and Neutral (0.51), reflected in the F1 score, highest for Positive sentiment at 0.79. With 174 Negative, 216 Neutral, and 333 Positive support counts, model achieved an overall accuracy of 0.69, effectively classifying Genshin Impact reviews based on sentiment. Analysis findings suggest a prevalence of positive opinions, indicating widespread player satisfaction with the game.