We carry out research in a range of tasks in sentiment analysis, including sentiment classification, emotion ranking, sentiment-topic extraction, Twitter sentiment analysis, dialogue emotion detection, emotion cause extraction, aspect-based sentiment analysis, stance detection and sarcasm detection.

Participants

Lin Gui, Gabriele Pergola, Hanqi Yan, Runcong Zhao, Lixing Zhu

Publications

Sentiment/emotion classification

• D. Zhou, M. Zhang, L. Zhang and Y. He. A Neural Group-wise Sentiment Analysis Model with Data Sparsity Awareness, The 35th AAAI Conference on Artificial Intelligence (AAAI), Feb. 2021.
• D. Zhou, M. Zhang, Y. Yang and Y. He. Hierarchical State Recurrent Neural Network for Social Emotion Ranking. Computer Speech & Language, Vol. 68, 101177, 2021.
• L. Gui, J. Leng, J. Zhou, R. Xu and Y. He. Multi-Task Learning with Mutual Learning for Joint Sentiment Classification and Topic Detection, IEEE Transactions on Knowledge and Data Engineering (TKDE), accepted.
• Y. Yang, D. Zhou, Y. He and M. Zhang. Interpretable Relevant Emotion Ranking with Event-Driven Attention. Conference on Empirical Methods in Natural Language Processing (EMNLP), Hong Kong, China, Nov. 2019.
• J. Du, L. Gui, Y. He, R. Xu and X. Wang. Convolution-Based Neural Attention with Applications to Sentiment Classification. IEEE Access, 7:27983 - 27992, 2019.
• D. Tang, Z. Zhang, Y. He, C. Lin and D. Zhou. Hidden Topic and Emotion Transition Model for Multi-Level Social Emotion Detection, Knowledge-Based Systems, 164:426-435, 2019.
• Y. Yang, D. Zhou and Y. He. An Interpretable Neural Network with Topical Information for Relevant Emotion Ranking. The 15th International Conference on Empirical Methods on Natural Language Processing (EMNLP), Brussel, Belgium, Oct. 2018.
• D. Zhou, Y. Yang and Y. He. Relevant Emotion Ranking from Text Constrained with Emotion Relationships, The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), New Orleans, Louisiana, USA, Jun. 2018.
• L. Gui, Y. Zhou, R. Xu, Y. He and Q. Lu, Learning Representations from Heterogeneous Network for Sentiment Classification of Product Reviews, Knowledge-Based Systems, 124:34-45, 2017.
• T. Chen, R. Xu, Y. He, X. Wang. Improving Sentiment Analysis via Sentence Type Classification using BiLSTM-CRF and CNN, Expert Systems with Applications, 72:221-230, 2017.
• L. Gui, R. Xu, Y. He, Q. Lu and Z. Wei. Intersubjectivity and Sentiment: from Language to Knowledge, The 25th International Joint Conference on Artificial Intelligence (IJCAI), New York, US, Jul. 2016.
• T. Chen, R. Xu, Y. He, Y. Xia, X. Wang. Learning User and Product Distributed Representations Using a Sequence Model for Sentiment Analysis, IEEE Computational Intelligence Magazine, 11(3):34-44, 2016.

Sentiment-topic analysis

• G. Pergola, L. Gui and Y. He. A Disentangled Adversarial Neural Topic Model for Separating Opinions from Plots in User Reviews, Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Jun. 2021.
• R. Zhao, L. Gui, G. Pergola and Y. He. Adversarial Learning of Poisson Factorisation Model for Gauging Brand Sentiment in User Reviews, The 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL), Apr. 2021.
• G. Pergola, L. Gui and Y. He. TDAM: a Topic-Dependent Attention Model for Sentiment Analysis. Information Processing and Management, 56(6):102084, 2019.

Twitter sentiment analysis

• L. Zhu, Z. Fang, G. Pergola, R. Procter and Y. He. Disentangled Learning of Stance and Aspect Topics for Vaccine Attitude Detection in Social Media. 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Jul. 2022.
• L. Zhu, Y. He and D. Zhou. Neural Temporal Opinion Modelling for Opinion Prediction on Twitter. 2020 Annual Conference of the Association for Computational Linguistics (ACL), Jul. 2020.
• L. Zhu, Y. He and D. Zhou. Neural Opinion Dynamics Model for the Prediction of User-Level Stance Dynamics. Information Processing and Management, 57(2):102031, 2020.
• L. Zhu, Y. He and D. Zhou. Hierarchical Viewpoint Discovery from Tweets Using Bayesian Modelling. Expert Systems with Applications, 116:430-438, 2019.
• H. Saif, Y. He, M. Fernandez and H. Alani. Contextual Semantics for Sentiment Analysis of Twitter. Information Processing & Management, 52(1):5-19, 2016.

Dialogue emotion detection

• L. Zhu, G. Pergola, L. Gui, D. Zhou and Y. He. Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detection, The 59th Annual Meeting of the Association for Computational Linguistics (ACL), Aug. 2021.

Emotion cause detection

• Yan, L. Gui, G. Pergola and Y. He. Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction, The 59th Annual Meeting of the Association for Computational Linguistics (ACL), Aug. 2021.
• C. Fan, C. Yuan, J. Du, L. Gui, M. Yang, R. Xu. Transition-based directed graph construction for emotion-cause pair extraction. 2020 Annual Conference of the Association for Computational Linguistics (ACL), Jul. 2020.
• L. Gui, J. Hu, Y. He, R. Xu, Q. Lu and J. Du. A Question Answering Approach for Emotion Cause Extraction. The 14th International Conference on Empirical Methods on Natural Language Processing (EMNLP), Copenhagen, Denmark, Sep. 2017.

Aspect-based sentiment analysis

• B. Liang, R. Yin, J. Du, L. Gui, Y. He, M. Yang and R. Xu. Embedding Refinement Framework for Targeted Aspect-based Sentiment Analysis, IEEE Transactions in Affective Computing, to appear.
• B. Liang, R. Yin, L. Gui, J. Du, Y. He and R. Xu. Aspect-Invariant Sentiment Feature Learning: Adversarial Multi-task Learning for Aspect-Based Sentiment Analysis, The 29th ACM International Conference on Information and Knowledge Management (CIKM), 2020.

Stance detection

• B. Liang, Q. Zhu, X. Li, M. Yang, L. Gui, Y. He and R. Xu. JointCL: A Joint Contrastive Learning Framework for Zero-Shot Stance Detection. The 60th Annual Meeting of the Association for Computational Linguistics (ACL), May 2022.
• B. Liang, Y. Fu, L. Gui, M. Yang, J. Du, Y. He and R. Xu.Target-adaptive Graph for Cross-target Stance Detection, The Web Conference (WWW), Apr. 2021.
• D. Vilares and Y. He. Detecting Perspectives in Political Debates. The 14th International Conference on Empirical Methods on Natural Language Processing (EMNLP), Copenhagen, Denmark, Sep. 2017.
• J. Du, R. Xu, Y. He and L. Gui. Stance Classification with Target-Specific Neural Attention, The 26th International Joint Conference on Artificial Intelligence (IJCAL), Melbourne, Australia, Aug. 2017.

Sarcasm detection / blame/praise detection

• B. Liang, C. Lou, X. Li, M. Yang, L. Gui, Y. He, W. Pei and R. Xu. Multi-Modal Sarcasm Detection via Cross-Modal Graph Convolutional Network. The 60th Annual Meeting of the Association for Computational Linguistics (ACL), May 2022.
• C. Lou, B. Liang, L. Gui, Y. He, Y. Dang and R. Xu. Affective Dependency Graph for Sarcasm Detection, The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Jul. 2021.
• U. Orizu and Y. He. Detecting Expressions of Blame or Praise in Text, The 10th edition of the Language Resources and Evaluation Conference (LREC), Portorož, Slovenia, May, 2016.

Early reviewer detection

• T. Bai, W.X. Zhao, Y. He, J-Y. Nie and J.-R. Wen. Characterizing and Predicting Early Reviewers for Effective Product Marketing on E-Commerce Websites. IEEE Transactions on Knowledge and Data Engineering, 30(12):2271-2284, 2018.