Publications

Spotlight papers

Recent trends in deep learning based natural language processing.
Tom Young, Devamanyu Hazarika, Soujanya Poria, and Erik Cambria.
IEEE Computational Intelligence Magazine.

Aspect extraction for opinion mining with a deep convolutional neural network.
Soujanya Poria, Erik Cambria, and Alexander Gelbukh.
Knowledge-Based Systems. (code)

Emotion recognition in conversation: Research challenges, datasets, and recent advances.
Soujanya Poria, Navonil Majumder, Rada Mihalcea, and Eduard Hovy.
IEEE Access 7.

Dialoguernn: An attentive rnn for emotion detection in conversations.
Navonil Majumder, Soujanya Poria, Devamanyu Hazarika, Rada Mihalcea, Alexander Gelbukh, and Erik Cambria.
AAAI 2019. (code)

Conversational memory network for emotion recognition in dyadic dialogue videos.
Devamanyu Hazarika, Soujanya Poria, Amir Zadeh, Erik Cambria, Louis-Philippe Morency, and Roger Zimmermann.
NAACL 2018. (code)

Dialoguegcn: A graph convolutional neural network for emotion recognition in conversation.
Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya, and Alexander Gelbukh.
NAACL 2018. (code)

MELD: A multimodal multi-party dataset for emotion recognition in conversations.
Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, Gautam Naik, Erik Cambria, and Rada Mihalcea.
ACL 2019. (code)

Sentiment analysis

Aspect extraction for opinion mining with a deep convolutional neural network
Soujanya Poria, Erik Cambria, and Alexander Gelbukh
Knowledge-Based Systems pdf

IARM: Inter-aspect relation modeling with memory networks in aspect-based sentiment analysis
Navonil Majumder, Soujanya Poria, Alexander Gelbukh, Md Shad Akhtar, Erik Cambria, and Asif Ekbal
EMNLP 2018 pdf

Modeling inter-aspect dependencies for aspect-based sentiment analysis
Devamanyu Hazarika, Soujanya Poria, Prateek Vij, Gangeshwar Krishnamurthy, Erik Cambria, and Roger Zimmermann
NAACL 2018 pdf

SenticNet 4: A semantic resource for sentiment analysis based on conceptual primitives
Erik Cambria, Soujanya Poria, Rajiv Bajpai, and Björn Schuller
COLING 2016 pdf

A rule-based approach to aspect extraction from product reviews
Soujanya Poria, Erik Cambria, Lun-Wei Ku, Chen Gui, and Alexander Gelbukh
In Proceedings of the second workshop on natural language processing for social media (SocialNLP), pp. 28-37. 2014. pdf

Enhanced SenticNet with affective labels for concept-based opinion mining
Soujanya Poria, Alexander Gelbukh, Amir Hussain, Newton Howard, Dipankar Das, and Sivaji Bandyopadhyay
IEEE Intelligent Systems pdf

Sentic patterns: Dependency-based rules for concept-level sentiment analysis
Soujanya Poria, Erik Cambria, Grégoire Winterstein, and Guang-Bin Huang
Knowledge-Based Systems 69 (2014): 45-63. pdf

Sentiment analysis is a big suitcase
Erik Cambria, Soujanya Poria, Alexander Gelbukh, and Mike Thelwall
IEEE Intelligent Systems 32, no. 6 (2017): 74-80. pdf

Sentiment data flow analysis by means of dynamic linguistic patterns
Soujanya Poria, Erik Cambria, Alexander Gelbukh, Federica Bisio, and Amir Hussain
IEEE Computational Intelligence Magazine 10, no. 4 (2015): 26-36. pdf

EmoSenticSpace: A novel framework for affective common-sense reasoning
Soujanya Poria, Alexander Gelbukh, Erik Cambria, Amir Hussain, and Guang-Bin Huang
Knowledge-Based Systems 69 (2014): 108-123. pdf

AffectiveSpace 2: Enabling affective intuition for concept-level sentiment analysis
Erik Cambria, Jie Fu, Federica Bisio, and Soujanya Poria
In Twenty-ninth AAAI conference on artificial intelligence. 2015. pdf

SenticNet 5: Discovering conceptual primitives for sentiment analysis by means of context embeddings
Erik Cambria, Soujanya Poria, Devamanyu Hazarika, and Kenneth Kwok
In Thirty-Second AAAI Conference on Artificial Intelligence. 2018. pdf

Concept-level sentiment analysis with dependency-based semantic parsing: a novel approach
Basant Agarwal, Soujanya Poria, Namita Mittal, Alexander Gelbukh, and Amir Hussain
Cognitive Computation 7, no. 4 (2015): 487-499. pdf

SeNTU: sentiment analysis of tweets by combining a rule-based classifier with supervised learning
Prerna Chikersal, Soujanya Poria, and Erik Cambria
In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pp. 647-651. 2015. pdf

Multilingual sentiment analysis: state of the art and independent comparison of techniques
Kia Dashtipour, Soujanya Poria, Amir Hussain, Erik Cambria, Ahmad YA Hawalah, Alexander Gelbukh, and Qiang Zhou
Cognitive computation 8, no. 4 (2016): 757-771. pdf

Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis
Soujanya Poria, Alexander Gelbukh, Erik Cambria, Peipei Yang, Amir Hussain, and Tariq Durrani
In 2012 IEEE 11th International Conference on Signal Processing, vol. 2, pp. 1251-1255. IEEE, 2012. pdf

Modelling public sentiment in Twitter: using linguistic patterns to enhance supervised learning
Prerna Chikersal, Soujanya Poria, Erik Cambria, Alexander Gelbukh, and Chng Eng Siong
In International Conference on Intelligent Text Processing and Computational Linguistics, pp. 49-65. Springer, Cham, 2015. pdf

Sentic LDA: Improving on LDA with semantic similarity for aspect-based sentiment analysis
Soujanya Poria, Iti Chaturvedi, Erik Cambria, and Federica Bisio
In 2016 international joint conference on neural networks (IJCNN), pp. 4465-4473. IEEE, 2016. pdf

Enriching SenticNet polarity scores through semi-supervised fuzzy clustering
Soujanya Poria, Alexander Gelbukh, Erik Cambria, Dipankar Das, and Sivaji Bandyopadhyay
In 2012 IEEE 12th International Conference on Data Mining Workshops, pp. 709-716. IEEE, 2012. pdf

Dependency-based semantic parsing for concept-level text analysis
Soujanya Poria, Basant Agarwal, Alexander Gelbukh, Amir Hussain, and Newton Howard
In International Conference on Intelligent Text Processing and Computational Linguistics, pp. 113-127. Springer, Berlin, Heidelberg, 2014. pdf

The CLSA model: A novel framework for concept-level sentiment analysis
Erik Cambria, Soujanya Poria, Federica Bisio, Rajiv Bajpai, and Iti Chaturvedi
In International Conference on Intelligent Text Processing and Computational Linguistics, pp. 3-22. Springer, Cham, 2015. pdf

OntoSenticNet: A commonsense ontology for sentiment analysis
Mauro Dragoni, Soujanya Poria, and Erik Cambria
IEEE Intelligent Systems 33, no. 3 (2018): 77-85. pdf

Sentic API: a common-sense based API for concept-level sentiment analysis
Erik Cambria, Soujanya Poria, Alexander Gelbukh, and Kenneth Kwok
(2014). pdf

Dependency tree-based rules for concept-level aspect-based sentiment analysis
Soujanya Poria, Nir Ofek, Alexander Gelbukh, Amir Hussain, and Lior Rokach
In Semantic Web Evaluation Challenge, pp. 41-47. Springer, Cham, 2014. pdf

Sentic Demo: A hybrid concept-level aspect-based sentiment analysis toolkit
Soujanya Poria, Alexander Gelbukh, B. Agarwal, E. Cambria, and N. Howard
ESWC 2014 (2014). pdf

Unsupervised commonsense knowledge enrichment for domain-specific sentiment analysis
Nir Ofek, Soujanya Poria, Lior Rokach, Erik Cambria, Amir Hussain, and Asaf Shabtai
Cognitive Computation 8, no. 3 (2016): 467-477. pdf

Bayesian deep convolution belief networks for subjectivity detection
Iti Chaturvedi, Erik Cambria, Soujanya Poria, and Rajiv Bajpai
In 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), pp. 916-923. IEEE, 2016. pdf

Developing a concept-level knowledge base for sentiment analysis in Singlish
Rajiv Bajpai, Soujanya Poria, Danyuan Ho, and Erik Cambria
In International Conference on Intelligent Text Processing and Computational Linguistics, pp. 347-361. Springer, Cham, 2016. pdf

A common-sense based api for concept-level sentiment analysis
Erik Cambria, Soujanya Poria, Alexander Gelbukh, and Kenneth Kwok
Making Sense of Microposts (# Microposts2014) (2014): 2. pdf

Phonetic-enriched Text Representation for Chinese Sentiment Analysis with Reinforcement Learning
Haiyun Peng, Yukun Ma, Soujanya Poria, Yang Li, and Erik Cambria
arXiv preprint arXiv:1901.07880 (2019). pdf

Dialogue systems/ Emotion recognition in conversations

Conversational memory network for emotion recognition in dyadic dialogue videos
Devamanyu Hazarika, Soujanya Poria, Amir Zadeh, Erik Cambria, Louis-Philippe Morency, and Roger Zimmermann
In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 2122-2132. 2018. pdf

Dialoguernn: An attentive rnn for emotion detection in conversations
Navonil Majumder, Soujanya Poria, Devamanyu Hazarika, Rada Mihalcea, Alexander Gelbukh, and Erik Cambria
In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 6818-6825. 2019. pdf

MELD: A multimodal multi-party dataset for emotion recognition in conversations
Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, Gautam Naik, Erik Cambria, and Rada Mihalcea
ACL (2019). pdf

ICON: interactive conversational memory network for multimodal emotion detection
Devamanyu Hazarika, Soujanya Poria, Rada Mihalcea, Erik Cambria, and Roger Zimmermann
In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 2594-2604. 2018. pdf

Emotion recognition in conversation: Research challenges, datasets, and recent advances
Soujanya Poria, Navonil Majumder, Rada Mihalcea, and Eduard Hovy
IEEE Access 7 (2019): 100943-100953. pdf

Dialoguegcn: A graph convolutional neural network for emotion recognition in conversation
Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya, and Alexander Gelbukh
arXiv preprint arXiv:1908.11540 (2019). pdf

Dialogue Systems with Audio Context
Tom Young, Vlad Pandelea, Soujanya Poria, and Erik Cambria
Neurocomputing (2020). pdf

Emotion Recognition in Conversations with Transfer Learning from Generative Conversation Modeling
Devamanyu Hazarika, Soujanya Poria, Roger Zimmermann, and Rada Mihalcea
arXiv preprint arXiv:1910.04980 (2019). pdf

Multimodal sentiment analysis

A review of affective computing: From unimodal analysis to multimodal fusion
Soujanya Poria, Erik Cambria, Rajiv Bajpai, and Amir Hussain
Information Fusion 37 (2017): 98-125. pdf

Fusing audio, visual and textual clues for sentiment analysis from multimodal content
Soujanya Poria, Erik Cambria, Newton Howard, Guang-Bin Huang, and Amir Hussain
Neurocomputing 174 (2016): 50-59. pdf

Deep convolutional neural network textual features and multiple kernel learning for utterance-level multimodal sentiment analysis
Soujanya Poria, Erik Cambria, and Alexander Gelbukh
In Proceedings of the 2015 conference on empirical methods in natural language processing, pp. 2539-2544. 2015. pdf

Convolutional MKL based multimodal emotion recognition and sentiment analysis
Soujanya Poria, Iti Chaturvedi, Erik Cambria, and Amir Hussain
In 2016 IEEE 16th international conference on data mining (ICDM), pp. 439-448. IEEE, 2016. pdf

Context-dependent sentiment analysis in user-generated videos
Soujanya Poria, Erik Cambria, Devamanyu Hazarika, Navonil Majumder, Amir Zadeh, and Louis-Philippe Morency
In Proceedings of the 55th annual meeting of the association for computational linguistics (volume 1: Long papers), pp. 873-883. 2017. pdf

Tensor fusion network for multimodal sentiment analysis
Amir Zadeh, Minghai Chen, Soujanya Poria, Erik Cambria, and Louis-Philippe Morency
EMNLP. (2017). pdf

Towards an intelligent framework for multimodal affective data analysis
Soujanya Poria, Erik Cambria, Amir Hussain, and Guang-Bin Huang
Neural Networks 63 (2015): 104-116. pdf

Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis
Soujanya Poria, Haiyun Peng, Amir Hussain, Newton Howard, and Erik Cambria
Neurocomputing 261 (2017): 217-230. pdf

Multi-attention recurrent network for human communication comprehension
Amir Zadeh, Paul Pu Liang, Soujanya Poria, Prateek Vij, Erik Cambria, and Louis-Philippe Morency
In Thirty-Second AAAI Conference on Artificial Intelligence. 2018. pdf

Memory fusion network for multi-view sequential learning
Amir Zadeh, Paul Pu Liang, Navonil Mazumder, Soujanya Poria, Erik Cambria, and Louis-Philippe Morency
In Thirty-Second AAAI Conference on Artificial Intelligence. 2018. pdf

Multimodal language analysis in the wild: Cmu-mosei dataset and interpretable dynamic fusion graph
AmirAli Bagher Zadeh, Paul Pu Liang, Soujanya Poria, Erik Cambria, and Louis-Philippe Morency
In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 2236-2246. 2018. pdf

Multimodal sentiment analysis using hierarchical fusion with context modeling
Navonil Majumder, Devamanyu Hazarika, Alexander Gelbukh, Erik Cambria, and Soujanya Poria
Knowledge-Based Systems 161 (2018): 124-133. pdf

Multi-level multiple attentions for contextual multimodal sentiment analysis
Soujanya Poria, Erik Cambria, Devamanyu Hazarika, Navonil Mazumder, Amir Zadeh, and Louis-Philippe Morency
In 2017 IEEE International Conference on Data Mining (ICDM), pp. 1033-1038. IEEE, 2017. pdf

Multimodal sentiment analysis: Addressing key issues and setting up the baselines
Soujanya Poria, Navonil Majumder, Devamanyu Hazarika, Erik Cambria, Alexander Gelbukh, and Amir Hussain
IEEE Intelligent Systems 33, no. 6 (2018): 17-25. pdf

Benchmarking multimodal sentiment analysis
Erik Cambria, Devamanyu Hazarika, Soujanya Poria, Amir Hussain, and R. B. V. Subramanyam
In International Conference on Computational Linguistics and Intelligent Text Processing, pp. 166-179. Springer, Cham, 2017. pdf

Contextual inter-modal attention for multi-modal sentiment analysis
Deepanway Ghosal, Md Shad Akhtar, Dushyant Chauhan, Soujanya Poria, Asif Ekbal, and Pushpak Bhattacharyya
In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 3454-3466. 2018. pdf

Multimodal sentiment analysis
Soujanya Poria, Amir Hussain, and Erik Cambria
Vol. 8. Cham, Switzerland: Springer, 2018. pdf

Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis
Md Shad Akhtar, Dushyant Singh Chauhan, Deepanway Ghosal, Soujanya Poria, Asif Ekbal, and Pushpak Bhattacharyya
arXiv preprint arXiv:1905.05812 (2019). pdf

Human multimodal language in the wild: A novel dataset and interpretable dynamic fusion model
Amir Zadeh, Paul Pu Liang, Soujanya Poria, Erik Cambria, and Louis-Philippe Morency
In Association for Computational Linguistics. 2018. pdf

Factorized Multimodal Transformer for Multimodal Sequential Learning
Amir Zadeh, Chengfeng Mao, Kelly Shi, Yiwei Zhang, Paul Pu Liang, Soujanya Poria, and Louis-Philippe Morency
arXiv preprint arXiv:1911.09826 (2019). pdf

WildMix Dataset and Spectro-Temporal Transformer Model for Monoaural Audio Source Separation
Amir Zadeh, Tianjun Ma, Soujanya Poria, and Louis-Philippe Morency
arXiv preprint arXiv:1911.09783 (2019). pdf

Variational Fusion for Multimodal Sentiment Analysis
Navonil Majumder, Soujanya Poria, Gangeshwar Krishnamurthy, Niyati Chhaya, Rada Mihalcea, and Alexander Gelbukh
arXiv preprint arXiv:1908.06008 (2019). pdf

Speaker-Independent Multimodal Sentiment Analysis for Big Data
Erik Cambria, Soujanya Poria, and Amir Hussain
In Multimodal Analytics for Next-Generation Big Data Technologies and Applications, pp. 13-43. Springer, Cham, 2019. pdf

Learning Visual Concepts in Images Using Temporal Convolutional Networks
Chen Qian, Iti Chaturvedi, Soujanya Poria, Erik Cambria, and Lorenzo Malandri
In 2018 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1280-1284. IEEE, 2018. pdf

Proceedings of Grand Challenge and Workshop on Human Multimodal Language (Challenge-HML)
Amir Zadeh, Paul Pu Liang, Louis-Philippe Morency, Soujanya Poria, Erik Cambria, and Stefan Scherer
In Proceedings of Grand Challenge and Workshop on Human Multimodal Language (Challenge-HML). 2018. pdf

NLP applications/ Machine learning

Recent trends in deep learning based natural language processing
Tom Young, Devamanyu Hazarika, Soujanya Poria, and Erik Cambria
ieee Computational intelligenCe magazine 13, no. 3 (2018): 55-75. pdf

Deep learning-based document modeling for personality detection from text
Navonil Majumder, Soujanya Poria, Alexander Gelbukh, and Erik Cambria
IEEE Intelligent Systems 32, no. 2 (2017): 74-79. pdf

Common sense knowledge based personality recognition from text
Soujanya Poria, Alexandar Gelbukh, Basant Agarwal, Erik Cambria, and Newton Howard
In Mexican International Conference on Artificial Intelligence, pp. 484-496. Springer, Berlin, Heidelberg, 2013. pdf

Fuzzy clustering for semi-supervised learning–case study: Construction of an emotion lexicon
Soujanya Poria, Alexander Gelbukh, Dipankar Das, and Sivaji Bandyopadhyay
In Mexican International Conference on Artificial Intelligence, pp. 73-86. Springer, Berlin, Heidelberg, 2012. pdf

Music genre classification: A semi-supervised approach
Soujanya Poria, Alexander Gelbukh, Amir Hussain, Sivaji Bandyopadhyay, and Newton Howard
In Mexican Conference on Pattern Recognition, pp. 254-263. Springer, Berlin, Heidelberg, 2013. pdf

Semantic textual entailment recognition using UNL
Partha Pakray, Soujanya Poria, Sivaji Bandyopadhyay, and Alexander Gelbukh
Polibits 43 (2011): 23-27. pdf

A Textual Entailment System using Anaphora Resolution
Partha Pakray, Snehasis Neogi, Pinaki Bhaskar, Soujanya Poria, Sivaji Bandyopadhyay, and Alexander F. Gelbukh
In TAC. 2011. pdf

JU_CSE_TAC: Textual Entailment Recognition System at TAC RTE-6
Partha Pakray, Santanu Pal, Soujanya Poria, Sivaji Bandyopadhyay, and Alexander F. Gelbukh
In TAC. 2010. pdf

A deep learning approach for multimodal deception detection
Gangeshwar Krishnamurthy, Navonil Majumder, Soujanya Poria, and Erik Cambria
arXiv preprint arXiv:1803.00344 (2018). pdf

A classifier based approach to emotion lexicon construction
Dipankar Das, Soujanya Poria, and Sivaji Bandyopadhyay
In International Conference on Application of Natural Language to Information Systems, pp. 320-326. Springer, Berlin, Heidelberg, 2012. pdf

Anaphora and coreference resolution: A review
Rhea Sukthanker, Soujanya Poria, Erik Cambria, and Ramkumar Thirunavukarasu
arXiv preprint arXiv:1805.11824 (2018). pdf

A review of artificial intelligence and biologically inspired computational approaches to solving issues in narrative financial disclosure
Saliha Minhas, Soujanya Poria, Amir Hussain, and Khalid Hussainey
In International Conference on Brain Inspired Cognitive Systems, pp. 317-327. Springer, Berlin, Heidelberg, 2013. pdf

Sentic computing for social media analysis, representation, and retrieval
Erik Cambria, Marco Grassi, Soujanya Poria, and Amir Hussain
In Social media retrieval, pp. 191-215. Springer, London, 2013. pdf

The Nitty–GRITties of Success: Computational Analysis of Grit From Language
Tushar Maheshwari, Aishwarya Reganti, Soujanya Poria, and Rada Mihalcea
IEEE Access 7 (2019): 179364-179372. pdf

An Attention-Based Model for Learning Dynamic Interaction Networks
Sandro Cavallari, Soujanya Poria, Erik Cambria, Vincent W. Zheng, and Hongyun Cai
In 2019 International Joint Conference on Neural Networks (IJCNN), pp. 1-8. IEEE, 2019. pdf

Sarcasm detection

Cascade: Contextual sarcasm detection in online discussion forums
Devamanyu Hazarika, Soujanya Poria, Sruthi Gorantla, Erik Cambria, Roger Zimmermann, and Rada Mihalcea
COLING (2018). pdf

A deeper look into sarcastic tweets using deep convolutional neural networks
Soujanya Poria, Erik Cambria, Devamanyu Hazarika, and Prateek Vij
COLING. (2016). pdf

Sentiment and sarcasm classification with multitask learning
Navonil Majumder, Soujanya Poria, Haiyun Peng, Niyati Chhaya, Erik Cambria, and Alexander Gelbukh
IEEE Intelligent Systems 34, no. 3 (2019): 38-43. pdf

Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)
Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, Roger Zimmermann, Rada Mihalcea, and Soujanya Poria
ACL. (2019). pdf