ABSA-PyTorch and Aspect-Based-Sentiment-Analysis
About ABSA-PyTorch
songyouwei/ABSA-PyTorch
Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析，使用PyTorch实现。
Implements both BERT-based models (BERT-SPC, LCF-BERT, AEN-BERT) and non-BERT architectures (ASGCN, LSTM variants, memory networks) for fine-grained sentiment classification, supporting k-fold cross-validation and inference pipelines. Leverages GloVe embeddings for traditional models and transformer pre-training for BERT variants, with modular training infrastructure compatible with scikit-learn for evaluation.
About Aspect-Based-Sentiment-Analysis
jiangqn/Aspect-Based-Sentiment-Analysis
A paper list for aspect based sentiment analysis.
This is a curated list of research papers and datasets focused on 'Aspect-Based Sentiment Analysis'. It helps researchers and data scientists understand and implement methods to automatically identify specific aspects of a product or service within text (like a 'screen' on a 'phone') and determine the sentiment expressed towards that aspect (e.g., 'the screen is bright'). It provides the foundational resources for building systems that can process raw text data, like customer reviews or social media posts, and output detailed sentiment insights tied to particular features.
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