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Explainable Sentiment Analysis

Explainable sentiment analysis pairs a sentiment classification model — typically a fine-tuned transformer such as BERT or RoBERTa — with a post-hoc or intrinsic explanation method (SHAP, LIME, attention visualization, or integrated gradients) that reveals which words, phrases, or features drove each prediction. The goal is both high predictive accuracy and transparent, auditable rationales for every label.

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Explainable Sentiment Analysis (XAI-augmented Opinion Mining)

Rekod kaedah taksonomik · ml-model / deep-learning

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Taxonomic bucketBERT-based Classificationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketExplainable BERT-based Classificationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRoBERTa-based Classificationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSentence Embeddingsmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketTopic Modelingmachine-suggested · Relational suggestion, not evidence.