Deep learning for sentiment analysis: A survey
Lei Zhang,Shuai Wang,Bing Liu +2 more
TLDR
Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state-of-the-art prediction results as mentioned in this paper, which is also popularly used in sentiment analysis in recent years.Abstract:
Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state-of-the-art prediction results. Along with the success of deep learning in many other application domains, deep learning is also popularly used in sentiment analysis in recent years. This paper first gives an overview of deep learning and then provides a comprehensive survey of its current applications in sentiment analysis.read more
Citations
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Deep Learning for Aspect-Based Sentiment Analysis: A Comparative Review
TL;DR: This article aims to provide a comparative review of deep learning for aspect-based sentiment analysis to place different approaches in context.
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ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis
TL;DR: An Attention-based Bidirectional CNN-RNN Deep Model (ABCDM) is proposed that achieves state-of-the-art results on both long review and short tweet polarity classification and is evaluated on sentiment polarity detection.
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FPGA-Based Accelerators of Deep Learning Networks for Learning and Classification: A Review
TL;DR: The techniques investigated in this paper represent the recent trends in the FPGA-based accelerators of deep learning networks and are expected to direct the future advances on efficient hardware accelerators and to be useful for deep learning researchers.
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Sentiment analysis based on deep learning: A comparative study
TL;DR: This paper reviews the latest studies that have employed deep learning to solve sentiment analysis problems, such as sentiment polarity, and models using term frequency-inverse document frequency and word embedding have been applied to a series of datasets.
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Finbert: financial sentiment analysis with pre-trained language models
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