논문KCI 등재
Hybrid deep learning-based models for social media sentiment analysis
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Our research paper emphasizesComparing the accuracy, precision, recall, and F1-score of hybrid models against standalone deep learning approaches (e.g., LSTM, CNN, BERT)
Abstract
Our research paper emphasizesComparing the accuracy, precision, recall, and F1-score of hybrid models against standalone deep learning approaches (e.g., LSTM, CNN, BERT)
관련 논문AI추천
A Text Sentiment Classification Method Based on LSTM-CNN신성윤, 이원주, Guangxing Wang한국컴퓨터정보학회 · 한국컴퓨터정보학회논문지2019 · 제24권 제12호Research on Chinese Microblog Sentiment Classification Based on TextCNN-BiLSTM ModelHaiqin Tang, Ruirui Zhang한국정보처리학회 · JIPS(Journal of Information Processing Systems)2023 · 제19권 제6호Cross-Domain Text Sentiment Classification Method Based on the CNN-BiLSTM-TE ModelLiang Yang, Ruirui Zhang, Sujuan Song, Yuyang Zeng한국정보처리학회 · JIPS(Journal of Information Processing Systems)2021 · 제17권 제4호Sentiment Analysis Main Tasks and Applications: A SurveyArafat Awajan, Sara Tedmori한국정보처리학회 · JIPS(Journal of Information Processing Systems)2019 · 제15권 제3호A Supervised Framework for Sentiment Analysis: A Two-Stage ApproachPrashantkumar M. Gavali, Suresh K. Shirgave인지과학연구소 · Journal of Cognitive Science2023 · 제24권 제3호Opinion Bias Detection Based on Social Opinions for Twitter권아롱, 이경순한국정보처리학회 · JIPS(Journal of Information Processing Systems)2013 · 제9권 제4호
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