Multimodal model links tourist images, reviews and ratings to satisfaction
A multimodal machine-learning system combining tourist images, reviews and ratings achieved 97.68% accuracy on a balanced benchmark while identifying comfort ...
A multimodal machine-learning system combining tourist images, reviews and ratings achieved 97.68% accuracy on a balanced benchmark while identifying comfort ...
An observational study of 12,493 Chinese social-media records linked deeper engagement with Xiaozhou Village to more frequent negative expression, without ...
A new leakage-controlled machine learning framework achieves strong sentiment classification on social media data while revealing that engagement prediction collapses ...
A computational study of six sentiment-analysis datasets found that OPIKNN and FOPIKNN improved average accuracy and macro F1-score over standard ...
A computational study of 7.4 million X posts found more negative original discourse about Venezuelan migration in Colombia after 2017–2018, ...
A five-year observational Weibo study identified seven categories and cyclical, event-driven, value-shaped and polarized patterns in Chinese university hot topics.
A transformer-autoencoder method that groups federated clients without labels improved sentiment-classification accuracy across controlled label-skew conditions on Sentiment140 and IMDB.
Researchers at Ghana's KNUST have released EduAffect, a 2,423-entry emotion-labelled dataset built from student social media posts and surveys that ...
A new text-mining study of online hospital reviews shows that patients judge medical care primarily on service attitude, convenience, and ...
A new neuro-symbolic framework called SymbolFusion applies explicit literary relation constraints to graph learning, achieving state-of-the-art performance in modeling symbolic ...
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© 2025 Scienmag - Science Magazine