# Sentiment/Text Classification

> Including **Sentiment Analysis**, **Opinion Target Extraction**, **Stance Detection** and **Text Classification** and etc.

## Text, Sentence and Document Classification
- [2014 EMNLP] **Convolutional Neural Networks for Sentence Classification**, [[paper]](https://arxiv.org/pdf/1408.5882.pdf), [[bibtex]](/Bibtex/Convolutional%20Neural%20Networks%20for%20Sentence%20Classification.bib) sources: [[yoonkim/CNN_sentence]](https://github.com/yoonkim/CNN_sentence), [[dennybritz/cnn-text-classification-tf]](https://github.com/dennybritz/cnn-text-classification-tf).
- [2015 ACL] **Deep Unordered Composition Rivals Syntactic Methods for Text Classification**, [[paper]](https://www.cs.umd.edu/~miyyer/pubs/2015_acl_dan.pdf), [[bibtex]](/Bibtex/Deep%20Unordered%20Composition%20Rivals%20Syntactic%20Methods%20for%20Text%20Classification.bib), [[slides]](https://pdfs.semanticscholar.org/7a5d/565e7abeb5e4570c1222dba0e5b1df18664a.pdf), sources: [[miyyer/dan]](https://github.com/miyyer/dan).
- [2015 AAAI] **Recurrent Convolutional Neural Networks for Text Classification**, [[paper]](https://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/view/9745/9552), [[bibtex]](/Bibtex/Recurrent%20Convolutional%20Neural%20Networks%20for%20Text%20Classification.bib), sources: [[knok/rcnn-text-classification]](https://github.com/knok/rcnn-text-classification), [[airalcorn2/Recurrent-Convolutional-Neural-Network-Text-Classifier]](https://github.com/airalcorn2/Recurrent-Convolutional-Neural-Network-Text-Classifier).
- [2016 NAACL] **Hierarchical Attention Networks for Document Classification**, [[paper]](https://www.cs.cmu.edu/%7Ediyiy/docs/naacl16.pdf), [[bibtex]](/Bibtex/Hierarchical%20Attention%20Networks%20for%20Document%20Classification.bib), sources: [[richliao/textClassifier]](https://github.com/richliao/textClassifier), [[ematvey/hierarchical-attention-networks]](https://github.com/ematvey/hierarchical-attention-networks).
- [2017 EACL] **Bag of Tricks for Efficient Text Classification**, [[paper]](https://arxiv.org/pdf/1607.01759.pdf), [[bibtex]](/Bibtex/Bag%20of%20Tricks%20for%20Efficient%20Text%20Classification.bib), sources: [[facebookresearch/fastText]](https://github.com/facebookresearch/fastText).
- [2017 ArXiv] **Which Encoding is the Best for Text Classification in Chinese, English, Japanese and Korean?**, [[paper]](https://arxiv.org/pdf/1708.02657.pdf), [[bibtex]](/Bibtex/Which%20Encoding%20is%20the%20Best%20for%20Text%20Classification%20in%20Chinese%20English%20Japanese%20and%20Korean.bib), sources: [[zhangxiangxiao/glyph]](https://github.com/zhangxiangxiao/glyph).
- [2018 ACL] **Multi-Task Label Embedding for Text Classification**, [[paper]](https://www.aclweb.org/anthology/D18-1484), [[bibtex]](/Bibtex/Multi-Task%20Label%20Embedding%20for%20Text%20Classification.bib), [[blog]](https://www.jianshu.com/p/4bbe061f0acd).
- [2017 ICLR] **Adversarial Training Methods For Semi-Supervised Text Classification**, [[paper]](https://arxiv.org/pdf/1605.07725.pdf), [[bibtex]](/Bibtex/Adversarial%20Training%20Methods%20for%20Semi-supervised%20Text%20Classification.bib), sources: [[TobiasLee/Text-Classification]](https://github.com/TobiasLee/Text-Classification).
- [2017 IJCNLP] **PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstracts**, [[paper]](http://aclweb.org/anthology/I17-2052), [[bibtex]](/Bibtex/PubMed%20200k%20RCT%20-%20a%20Dataset%20for%20Sequential%20Sentence%20Classification%20in%20Medical%20Abstracts.bib), sources: [[Franck-Dernoncourt/pubmed-rct]](https://github.com/Franck-Dernoncourt/pubmed-rct).
- [2017 ACL] **Adversarial Multi-task Learning for Text Classification**, [[paper]](http://www.aclweb.org/anthology/P17-1001), [[bibtex]](/Bibtex/Adversarial%20Multi-task%20Learning%20for%20Text%20Classification.bib), sources: [[FrankWork/fudan_mtl_reviews]](https://github.com/FrankWork/fudan_mtl_reviews).
- [2018 NLPCC] **Densely Connected Bidirectional LSTM with Applications to Sentence Classification**, [[paper]](https://arxiv.org/pdf/1802.00889.pdf), [[bibtex]](/Bibtex/Densely%20Connected%20Bidirectional%20LSTM%20with%20Applications%20to%20Sentence%20Classification.bib), source: [[IsaacChanghau/Dense_BiLSTM]](https://github.com/IsaacChanghau/Dense_BiLSTM).
- [2018 NAACL] **Multinomial Adversarial Networks for Multi-Domain Text Classification**, [[paper]](http://aclweb.org/anthology/N18-1111), [[bibtex]](/Bibtex/Multinomial%20Adversarial%20Networks%20for%20Multi-Domain%20Text%20Classification.bib) sources: [[ccsasuke/man]](https://github.com/ccsasuke/man).
- [2018 ACL] **Joint Embedding of Words and Labels for Text Classification**, [[paper]](https://www.aclweb.org/anthology/P18-1216), [[bibtex]](/Bibtex/Joint%20Embedding%20of%20Words%20and%20Labels%20for%20Text%20Classification.bib), [[poster]](https://www.aclweb.org/anthology/attachments/P18-1216.Poster.pdf), [[blog]](https://zhuanlan.zhihu.com/p/54734708), sources: [[guoyinwang/LEAM]](https://github.com/guoyinwang/LEAM).
- [2018 EMNLP] **Hierarchical Neural Networks for Sequential Sentence Classification in Medical Scientific Abstracts**, [[paper]](http://aclweb.org/anthology/D18-1349), [[bibtex]](/Bibtex/Hierarchical%20Neural%20Networks%20for%20Sequential%20Sentence%20Classification%20in%20Medical%20Scientific%20Abstracts.bib).
- [2018 EMNLP] **MCapsNet: Capsule Network for Text with Multi-Task Learning**, [[paper]](https://www.aclweb.org/anthology/D18-1486.pdf), [[bibtex]](/Bibtex/MCapsNet%20-%20Capsule%20Network%20for%20Text%20with%20Multi-Task%20Learning.bib).
- [2019 AAAI] **Graph Convolutional Networks for Text Classification**, [[paper]](https://arxiv.org/pdf/1809.05679.pdf), [[bibtex]](/Bibtex/Graph%20Convolutional%20Networks%20for%20Text%20Classification.bib), sources: [[yao8839836/text_gcn]](https://github.com/yao8839836/text_gcn).
- [2021 ACL] **Counterfactual Inference for Text Classification Debiasing**, [[paper]](https://aclanthology.org/2021.acl-long.422.pdf), [[bibtex]](/Bibtex/Counterfactual%20Inference%20for%20Text%20Classification%20Debiasing.bib), sources: [[qianc62/Corsair]](https://github.com/qianc62/Corsair).

## Sentiment Analysis
- **Introduction to Sentiment Analysis**, [[slides]](https://lct-master.org/files/MullenSentimentCourseSlides.pdf), [[blog]](https://blog.algorithmia.com/introduction-sentiment-analysis-algorithms/).
- [2013 EMNLP] **Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank**, [[paper]](https://nlp.stanford.edu/~socherr/EMNLP2013_RNTN.pdf), [[bibtex]](https://www.aclweb.org/anthology/D13-1170.bib), sources: [[rksltnl/RNTN]](https://github.com/rksltnl/RNTN), [[awni/semantic-rntn]](https://github.com/awni/semantic-rntn), [[rgobbel/rntn]](https://github.com/rgobbel/rntn).
- [2014 ACL] **A Convolutional Neural Network for Modelling Sentences**, [[paper]](https://arxiv.org/pdf/1404.2188.pdf), [[bibtex]](https://www.aclweb.org/anthology/P14-1062.bib), sources: [[hritik25/Dynamic-CNN-for-Modelling-Sentences]](https://github.com/hritik25/Dynamic-CNN-for-Modelling-Sentences), [[FredericGodin/DynamicCNN]](https://github.com/FredericGodin/DynamicCNN).
- [2015 EMNLP] **Deep Convolutional Neural Network Textual Features and Multiple Kernel Learning for Utterance-Level Multimodal Sentiment Analysis**, [[paper]](https://www.aclweb.org/anthology/D/D15/D15-1303.pdf), [[bibtex]](https://www.aclweb.org/anthology/D15-1303.bib).
- [2015 ACL] **Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks**, cover _semantic relatedness and sentiment classification_ tasks. [[paper]](https://www.aclweb.org/anthology/P15-1150.pdf), [[bibtex]](https://www.aclweb.org/anthology/P15-1150.bib), sources: [[stanfordnlp/treelstm]](https://github.com/stanfordnlp/treelstm), [[nicolaspi/treelstm]](https://github.com/nicolaspi/treelstm), [[sapruash/RecursiveNN]](https://github.com/sapruash/RecursiveNN), [[dallascard/TreeLSTM]](https://github.com/dallascard/TreeLSTM).
- [2016 EMNLP] **A Hierarchical Model of Reviews for Aspect-based Sentiment Analysis**, [[paper]](https://arxiv.org/pdf/1609.02745.pdf), [[bibtex]](https://www.aclweb.org/anthology/D16-1103.bib).
- [2016 EMNLP] **Attention-based LSTM for Aspect-level Sentiment Classification**, [[paper]](https://aclweb.org/anthology/D16-1058), [[bibtex]](https://www.aclweb.org/anthology/D16-1058.bib), sources: [[scaufengyang/TD-LSTM]](https://github.com/scaufengyang/TD-LSTM).
- [2016 ICDM] **Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis**, [[paper]](http://sentic.net/convolutional-mkl-based-multimodal-sentiment-analysis.pdf), [[bibtex]](/Bibtex/Convolutional%20MKL%20Based%20Multimodal%20Emotion%20Recognition%20and%20Sentiment%20Analysis.bib), sources: [[SenticNet/multimodal-sentiment-detection]](https://github.com/SenticNet/multimodal-sentiment-detection).
- [2017 ACL] **Learning When to Skim and When to Read**, [[paper]](http://www.aclweb.org/anthology/W17-2631), [[bibtex]](https://www.aclweb.org/anthology/W17-2631.bib), [[blog]](https://einstein.ai/research/learning-when-to-skim-and-when-to-read).
- [2017 ICME] **Select-additive Learning: Improving Generalization in Multimodal Sentiment Analysis**, [[paper]](https://arxiv.org/pdf/1609.05244.pdf), [[bibtex]](/Bibtex/Select-additive%20Learning.bib), sources: [[HaohanWang/SelectAdditiveLearning]](https://github.com/HaohanWang/SelectAdditiveLearning).
- [2017 ICMI] **Multimodal Sentiment Analysis with Word-Level Fusion and Reinforcement Learning**, [[paper]](http://www.cs.cmu.edu/~pliang/papers/icmi2017-gme-camera.pdf), [[bibtex]](/Bibtex/Multimodal%20Sentiment%20Analysis%20with%20Word-Level%20Fusion%20and%20Reinforcement%20Learning.bib).
- [2017 SIGIR] **Multitask Learning for Fine-Grained Twitter Sentiment Analysis**, [[paper]](https://arxiv.org/pdf/1707.03569.pdf), [[bibtex]](/Bibtex/Multitask%20Learning%20for%20Fine-Grained%20Twitter%20Sentiment%20Analysis.bib), sources: [[balikasg/sigir2017]](https://github.com/balikasg/sigir2017).
- [2017 EMNLP] **Tensor Fusion Network for Multimodal Sentiment Analysis**, [[paper]](https://www.aclweb.org/anthology/D17-1115), [[bibtex]](https://www.aclweb.org/anthology/D17-1115.bib), sources: [[A2Zadeh/TensorFusionNetwork]](https://github.com/A2Zadeh/TensorFusionNetwork).
- [2017 ACL] **Context-Dependent Sentiment Analysis in User-Generated Videos**, [[paper]](http://sentic.net/context-dependent-sentiment-analysis-in-user-generated-videos.pdf), [[bibtex]](https://www.aclweb.org/anthology/P17-1081.bib), sources: [[SenticNet/contextual-sentiment-analysis]](https://github.com/SenticNet/contextual-sentiment-analysis).
- [2018 ACL] **Multiple Instance Learning Networks for Fine-Grained Sentiment Analysis**, [[paper]](https://arxiv.org/pdf/1711.09645.pdf), [[bibtex]](https://www.aclweb.org/anthology/Q18-1002.bib), [[data]](https://github.com/EdinburghNLP/spot-data).
- [2018 AAAI] **Targeted Aspect-Based Sentiment Analysis via Embedding Commonsense Knowledge into an Attentive LSTM**, [[paper]](http://sentic.net/sentic-lstm.pdf), [[bibtex]](/Bibtex/Targeted%20Aspect-Based%20Sentiment%20Analysis%20via%20Embedding%20Commonsense%20Knowledge%20into%20an%20Attentive%20LSTM.bib).
- [2018 Cognitive Computation] **Sentic LSTM: a Hybrid Network for Targeted Aspect-Based Sentiment Analysis**, [[paper]](https://link.springer.com/article/10.1007/s12559-018-9549-x), [[bibtex]](/Bibtex/Sentic%20LSTM.bib), sources: [[SenticNet/sentic-lstm]](https://github.com/SenticNet/sentic-lstm).
- [2018 WWW] **Sentiment Analysis by Capsules**, [[paper]](https://pdfs.semanticscholar.org/e856/f875c7b72534850c2a31329e748bd656f14e.pdf?_ga=2.192355946.1970988380.1587960315-427987589.1587960315), [[bibtex]](/Bibtex/Sentiment%20Analysis%20by%20Capsules.bib).
- [2019 ACL] **Multi-Source Cross-Lingual Model Transfer: Learning What to Share**, [[paper]](https://www.aclweb.org/anthology/P19-1299), [[bibtex]](/Bibtex/Multi-Source%20Cross-Lingual%20Model%20Transfer%20-%20Learning%20What%20to%20Share.bib), sources: [[microsoft/Multilingual-Model-Transfer]](https://github.com/microsoft/Multilingual-Model-Transfer).
- [2019 ACL] **Towards Fine-grained Text Sentiment Transfer**, [[paper]](https://www.aclweb.org/anthology/P19-1194.pdf), [[bibtex]](/Bibtex/Towards%20Fine-grained%20Text%20Sentiment%20Transfer.bib), sources: [[luofuli/Fine-grained-Sentiment-Transfer]](https://github.com/luofuli/Fine-grained-Sentiment-Transfer).
- [2020 ICLR] **Learning the Difference that Makes a Difference with Counterfactually-Augmented Data**, [[paper]](https://openreview.net/pdf?id=Sklgs0NFvr), [[bibtex]](/Bibtex/Learning%20the%20Difference%20that%20Makes%20a%20Difference%20with%20Counterfactually-Augmented%20Data.bib), sources: [[dkaushik96/counterfactually-augmented-data]](https://github.com/dkaushik96/counterfactually-augmented-data).
- [2020 ACL] **Pretrained Transformers Improve Out-of-Distribution Robustness**, [[paper]](https://aclanthology.org/2020.acl-main.244.pdf), [[bibtex]](/Bibtex/Pretrained%20Transformers%20Improve%20Out-of-Distribution%20Robustness.bib), sources: [[camelop/NLP-Robustness]](https://github.com/camelop/NLP-Robustness).
- [2021 ArXiv] **Interventional Aspect-Based Sentiment Analysis**, [[paper]](https://arxiv.org/pdf/2104.11681.pdf), [[bibtex]](/Bibtex/Interventional%20Aspect-Based%20Sentiment%20Analysis.bib), sources: [[zjunlp/SENTA]](https://github.com/zjunlp/SENTA).

## Opinion Target Extraction & Target Sentiment Prediction
- [2017 AAAI] **Recurrent Neural Networks with Auxiliary Labels for Cross-Domain Opinion Target Extraction**, [[paper]](https://pdfs.semanticscholar.org/d083/41562091ac6777f613a68a0d59eb600b5c57.pdf), [[bibtex]](/Bibtex/Recurrent%20Neural%20Networks%20with%20Auxiliary%20Labels%20for%20Cross-Domain%20Opinion%20Target%20Extraction.bib). 
- [2019 AAAI] **A Unified Model for Opinion Target Extraction and Target Sentiment Prediction**, [[paper]](https://arxiv.org/pdf/1811.05082.pdf), [[bibtex]](/Bibtex/A%20Unified%20Model%20for%20Opinion%20Target%20Extraction%20and%20Target%20Sentiment%20Prediction.bib), [[slides]](https://lixin4ever.github.io/paper/AAAI2019/slides/aaai19_lixin_slides.pdf), sources: [[lixin4ever/E2E-TBSA]](https://github.com/lixin4ever/E2E-TBSA).
- [2019 ACL] **An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis**, [[paper]](https://www.aclweb.org/anthology/P19-1048), [[bibtex]](/Bibtex/An%20Interactive%20Multi-Task%20Learning%20Network%20for%20End-to-End%20Aspect-Based%20Sentiment%20Analysis.bib), sources: [[ruidan/IMN-E2E-ABSA]](https://github.com/ruidan/IMN-E2E-ABSA).
- [2019 IJCAI] **A Span-based Joint Model for Opinion Target Extraction and Target Sentiment Classification**, [[paper]](https://www.ijcai.org/proceedings/2019/0762.pdf), [[bibtex]](/Bibtex/A%20Span-based%20Joint%20Model%20for%20Opinion%20Target%20Extraction%20and%20Target%20Sentiment%20Classification.bib).

## Stance Detection
- [2017 TOIT] **Stance and Sentiment in Tweets**, [[paper]](https://arxiv.org/pdf/1605.01655.pdf), [[bibtex]](/Bibtex/Stance%20and%20Sentiment%20in%20Tweets.bib).
- [2016 SemEval] **SemEval-2016 Task 6: Detecting Stance in Tweets**, [[paper]](http://www.aclweb.org/anthology/S16-1003), [[bibtex]](https://www.aclweb.org/anthology/S16-1003.bib), [[homepage]](http://alt.qcri.org/semeval2016/task6/), [[The SemEval-2016 Stance Dataset]](http://www.saifmohammad.com/WebPages/StanceDataset.htm).
- [2016 SemEval] **DeepStance at SemEval-2016 Task 6: Detecting Stance in Tweets Using Character and Word-Level CNNs**, [[paper]](https://www.aclweb.org/anthology/S16-1067.pdf), [[bibtex]](https://www.aclweb.org/anthology/S16-1067.bib).
- [2016 SemEval] **Detecting Stance in Tweets And Analyzing its Interaction with Sentiment**, [[paper]](https://www.aclweb.org/anthology/S16-2021.pdf), [[bibtex]](https://www.aclweb.org/anthology/S16-2021.bib), sources: [[vishaalmohan/twitter-stance-detection]](https://github.com/vishaalmohan/twitter-stance-detection).
- [2018 ECIR] **Topical Stance Detection for Twitter: A Two-Phase LSTM Model Using Attention**, [[paper]](https://arxiv.org/pdf/1801.03032.pdf), [[bibtex]](/Bibtex/Topical%20Stance%20Detection%20for%20Twitter.bib).