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Publication Detailed Description
Comparison between sentiment analysis approaches applied to digital games
2023 18th Iberian Conference on Information Systems and Technologies (CISTI)
Year (definitive publication)
2023
Language
English
Country
United States of America
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Alternative Titles
(Portuguese) Comparação de abordagens de análise de sentimentos aplicadas em jogos digitais
Abstract
his article presents an analysis of sentiment classification algorithms, based on texts in Portuguese (Pt-Br) extracted from Twitter and Steam platforms, to determine which are the best Analysis Sentiment algorithms to classify user feedback in digital game contexts. On the Twitter platform, the best algorithm was Stacking with Support Vector Machine meta- classifier reaching 81.5% Accuracy. On the Steam platform, the best algorithm was Stacking with Random Forest meta-classifier reaching 82.8% Accuracy. The results show that the performance of each algorithm tends to improve when using Steam data.
Acknowledgements
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Keywords
Análise de sentimentos,Support vector machine,Stacking with random forest
Fields of Science and Technology Classification
- Computer and Information Sciences - Natural Sciences
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