HIGHLIGHTS
- What: The study introduced an innovative approach to sentiment analysis on mobile gaming data obtained from Twitter. This approach allowed the models to focus on the most salient words, facilitating a more accurate analysis. In this study, sentiment analysis on tweets related to mobile games was conducted through a comprehensive approach that involved data collection, preprocessing, feature extraction, and the application of various machine_learning algorithms. This study evaluated various machine_learning models for sentiment classification in mobile games, with an emphasis on English and Turkish datasets.
- Who: SETSCI Conference and colleagues from the Özalp Vocational School . . .
If you want to have access to all the content you need to log in!
Thanks :)
If you don't have an account, you can create one here.