{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T17:58:50Z","timestamp":1772906330338,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685380","type":"print"},{"value":"9781643685397","type":"electronic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,18]]},"abstract":"<jats:p>This research introduces a novel dataset of user reviews in the mobile gaming domain, comprising over 251,000 reviews spanning 72 game types gathered from the Google Play Store. Leveraging advanced natural language processing (NLP) techniques, the dataset undergoes processing to serve as a valuable resource for developing sentiment analysis models. Additionally, this paper presents a new approach utilizing Transformer models for the sentiment analysis problem on this dataset, explicitly focusing on overall sentiment classification into Positive, Negative, or Neutral categories. In this paper, we incorporate emoji data into sentiment classification. The experimental results demonstrate that the inclusion of emojis leads to improved performance. Specifically, the RoBERTa model achieves the highest performance on the emojis dataset, with an Accuracy of 0.942, Loss of 0.146, and F1 Scores for Positive, Neutral, and Negative sentiments at 0.970, 0.800, and 0.930, respectively.<\/jats:p>","DOI":"10.3233\/faia240384","type":"book-chapter","created":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T07:57:29Z","timestamp":1726819049000},"source":"Crossref","is-referenced-by-count":2,"title":["Sentiment Classification in Mobile Gaming Reviews: Customized Transformer Models with Emojis Retained"],"prefix":"10.3233","author":[{"given":"Minh Tri","family":"Doan","sequence":"first","affiliation":[{"name":"Ho Chi Minh City University of Education, Ho Chi Minh City, 700000, Vietnam"}]},{"given":"Minh Phuong","family":"Dam","sequence":"additional","affiliation":[{"name":"University of Science, Ho Chi Minh City, 700000, Vietnam"},{"name":"Vietnam National University Ho Chi Minh City, 700000, Vietnam"}]},{"given":"Tram T.","family":"Doan","sequence":"additional","affiliation":[{"name":"University of Science, Ho Chi Minh City, 700000, Vietnam"},{"name":"Vietnam National University Ho Chi Minh City, 700000, Vietnam"}]},{"given":"Hung","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Ho Chi Minh City University of Education, Ho Chi Minh City, 700000, Vietnam"}]},{"given":"Binh T.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"University of Science, Ho Chi Minh City, 700000, Vietnam"},{"name":"Vietnam National University Ho Chi Minh City, 700000, Vietnam"},{"name":"AISIA Research Lab, Ho Chi Minh City, Vietnam"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","New Trends in Intelligent Software Methodologies, Tools and Techniques"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA240384","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T07:57:30Z","timestamp":1726819050000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA240384"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,18]]},"ISBN":["9781643685380","9781643685397"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia240384","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,18]]}}}