awesome nlp sentiment analysis

awesome-nlp-sentiment-analysis

Collect data sets, papers, open source implementations related to the NLP field, especially sentiment analysis, emotional cause recognition, evaluation objects and evaluation word extraction.

Papers & ? Codes

Sentiment Analysis

1. Deep Learning for Sentiment analysis: A Survey. paper

Emotional attribution

1. An Ensemble Approach for Emotion Cause Detection with Event Extraction and Multi-Kernel SVMs. paper

2. Event-Driven Emotion Cause Extraction with Corpus Construction. paper

3. A Question Answering Approach to Emotion Cause Extraction. paper

4. A Bootstrap Method for Automatic Rule Acquisition on Emotion Cause Extraction. paper

5. Emotion Cause Detection for Chinese Micro-Blogs Based on ECOCC Model. paper

6. Emotion Cause Detection with Linguistic Constructions. paper

7. Emotion Cause Extraction, A Challenging Task with Corpus Construction. paper

8. Extracting Causes of Emotions from Text. paper

9. Emotional cause recognition method based on E-CNN neural network. paper

10. Emotional cause recognition method based on sequence labeling model. paper

11. Research on automatic emotional attribution method based on text. paper

12. A Co-Attention Neural Network Model for Emotion Cause Analysis with Emotional Context Awareness. paper

13. Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in Texts. paper code

Evaluation object and evaluation word extraction

4. Fine-grained Opinion Mining with Recurrent Neural Networks and Word Embeddings. paper code

5. Character-based BiLSTM-CRF Incorporating POS and Dictionaries for Chinese Opinion Target Extraction. paper code

6. A Unified Model for Opinion Target Extraction and Target Sentiment Prediction. paper code

7. Review of the study of the extraction of evaluation objects. paper

8. Use the depth-length and short-time memory model for joint extraction of evaluation words and evaluation objects. paper

9. Research on the extraction of comment objects based on semantic and syntactic dependencies. paper

10. Default item identification of evaluation object based on conditional random field. paper

11. Research on Chinese Weibo evaluation object extraction based on CRFs and domain ontology. paper

12. Research on emotional tendency analysis methods based on Weibo. paper

13. Research on evaluation objects and polarity extraction based on iterative two-step CRF model. paper

14. Research on the method of extracting evaluation objects based on syntactic features. paper

15. Chinese sentence evaluation object extraction based on cascading CRFs. paper

16. Extraction and discrimination of evaluation objects and their tendencies. paper

17. Evaluation object emotional clustering based on non-complete information system. paper

18. Study on the extraction characteristics of evaluation objects based on CRFs. paper

19. Extraction of evaluation objects based on core sentences and syntactic relationships. paper

20. Research on automatic identification of product evaluation objects for specific fields. paper

21. Evaluation object extraction and its tendency analysis. paper

22. Aspect extraction for opinion mining with a deep convolutional neural network. paper

23. Recursive neural conditional random fields for aspect-based sentiment analysis. paper

24. Coupled multi-layer attentions for co-extraction of aspect and opinion terms. paper

? Dataset

Evaluation object and evaluation word extraction

• SemEval-2014 Task 4

• Chinese Weibo sentiment analysis evaluation data

• Baidu, Mafengwo and Dianping datasets

• Emotional Causes to Dataset