Publications

Journals

  1. S. Poria, E. Cambria, L. Bhaskaran, R. Bajpai and A. Hussain. New Avenues in Affective Computing: from Unimodal Analysis to Multimodal Fusion. In: Information Fusion (2017).

  2. S. Poria, H. Peng, E. Cambria, A. Hussain, N. Howard. Ensemble Application of Convolutional Neural Networks and Multiple Kernel Learning for Multimodal Sentiment Analysis. In Neurocomputing (2016).

  3. Dashtipour, K., Poria, S., Hussain, A., Cambria, E., Hawalah, A.Y., Gelbukh, A. and Zhou, Q., Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques. Cognitive Computation, pp.1-15, (2016).

  4. S. Poria, E. Cambria and Gelbukh, A., Aspect extraction for opinion mining with a deep convolutional neural network. Knowledge-Based Systems, 108, pp. 42-49, (2016).

  5. S. Poria, A. Hussain, E. Cambria. Fusing Audio, Visual and Textual Clues for Big Social Data Analysis. Neurocomputing (2016).

  6. N. Ofek, S. Poria, L. Rokach, E. Cambria, A. Hussain, A. Shabtai. Unsupervised Commonsense Knowledge Enrichment for Domain-Specific Sentiment Analysis. Springer Cognitive Computation, in press (2016).

  7. S. Poria, E. Cambria, F. Bisio, A. Gelbukh, A. Hussain. Sentiment Data Flow Analysis by Means of Dynamic Linguistic Patterns for Concept-Based Opinion Mining. IEEE Computational Intelligence Magazine, in press (2015).

  8. S. Poria, E. Cambria, A. Hussain, G.-B. Huang. Towards an Intelligent Framework for Multimodal Affective Data Analysis. Neural Networks (2015).

  9. B. Agarwal, S. Poria, E. Cambria, N. Mittal, A. Gelbukh, A. Hussain. Concept Level Sentiment Analysis using Dependency-based Semantic Parsing. Cognitive Computation (2015).

  10. S. Poria, A. Gelbukh, E. Cambria, A. Hussain, G.-B. Huang. EmoSenticSpace: A Novel Framework for Affective Common-sense Reasoning. Knowledge-Based Systems, Special Issue on Big Data for SocialAnalysis (2014).

  11. S. Poria, E. Cambria, G. Winterstein, G.-B. Huang. Sentic patterns: Dependency-based Rules for Concept level Sentiment Analysis. Knowledge-Based Systems, Special Issue on Big Data for Social Analysis (2014).

  12. S. Poria, A. Gelbukh, A. Hussain, D. Das, S. Bandopadhyay. Enhanced SenticNet with Affective Labels for Concept-based Opinion Mining. IEEE Intelligent Systems, ISSN 15411672, 2013.

  13. P. Pakray, S. Poria, A. Gelbukh, S. Bandyopadhyay. Semantic Textual Entailment Recognition using UNL. Polibits, Special Issue on Computational Linguistics and Intelligent Text Processing (2011).

  14. E. Cambria, M. Grassi, S. Poria, A. Hussain. Sentic Computing for Social Media Analysis, Representation, and Retrieval. Book chapter. In: Social Media Retrieval. Network and Communication book series, Springer, ISBN 978-1-4471-4555-4, 2013.

  15. Conferences

  16. S. Poria, E. Cambria, D. Hazarika, N. Mazumder, A. Zadeh, and LP. Morency. Context-Dependent Sentiment Analysis in User-Generated Videos. In Association for Computational Linguistics (ACL), 2017.

  17. S. Poria, E. Cambria, D. Hazarika, and P. Vij. A deeper look into sarcastic tweets using deep convolutional neural networks. In: COLING, Osaka (2016)

  18. S. Poria, I. Chaturvedi, E. Cambria, and A. Hussain. Convolutional MKL based multimodal emotion recognition and sentiment analysis. In: ICDM, Barcelona (2016)

  19. E. Cambria, S. Poria, R. Bajpai, and B. Schuller. SenticNet 4: A semantic resource for sentiment analysis based on conceptual primitives. In: COLING, Osaka (2016)

  20. R. Bajpai, S. Poria, D. Ho, and E. Cambria. Developing a concept-level knowledge base for sentiment analysis in Singlish. In: CICLing, Konya (2016)

  21. S. Poria, I. Chaturvedi, E. Cambria, and F. Bisio. Sentic LDA: Improving on LDA with semantic similarity for aspect-based sentiment analysis. In: IJCNN 2016, Vancouver.

  22. S. Poria, E. Cambria, and A. Gelbukh. Deep Convolutional Neural Network Textual Features and Multiple Kernel Learning for Utterance-Level Multimodal Sentiment Analysis. EMNLP 2015. Lisbon, Portugal.

  23. E. Cambria, J. Fu, F. Bisio, and S. Poria. AffectiveSpace 2: Enabling affective intuition for concept level sentiment analysis. AAAI 2015. Austin, USA.

  24. P. Chikersal, S. Poria, E. Cambria, A. Gelbukh, C. E. Siong. Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning. CICLing 2015, Cairo, Egypt. Springer LNCS.

  25. E. Cambria, S. Poria, F. Bisio, R. Bajpai and I. Chaturvedi. The CLSA Model: A Novel Framework for Concept-Level Sentiment Analysis. CICLing 2015, Cairo, Egypt. Springer LNCS.

  26. S. Poria, B. Agarwal, A. Gelbukh, A. Hussain, N. Howard. Dependency-based Semantic Parsing for Concept-level Text Analysis. CICLing 2014, Kathmandu, Nepal. Springer LNCS.

  27. E. Cambria, S. Poria, A. Gelbukh, K. Kwok. A Common-Sense Based API for ConceptLevel Sentiment Analysis. WWW 2014, Making Sense of Microposts Microposts. Seoul, Korea

  28. S. Poria, E. Cambria, L.-W. Ku, C. Gui, A. Gelbukh. A Rule-Based Approach to Aspect Extraction from Product Reviews. SocialNLP at COLING 2014, Dublin, Ireland, invited paper.

  29. S. Poria, N. Ofek, A. Gelbukh, A. Hussain, L. Rokach. Dependency Tree-based Rules for Concept-Level Aspect-based Sentiment Analysis. SemWebEval 2014 at ESWC 2014, Crete, Grece, Springer CCIS.

  30. S. Minhas, S. Poria, A. Hussain, K. Hussainey. A Review of Artificial Intelligence and Biologically Inspired Computational Approaches to Solving Issues in Narrative Financial Disclosure. BICS 2013, Beijing, China, Springer LNAI.

  31. S. Poria, A. Gelbukh, B. Agarwal, E. Cambria, N Howard. Common sense knowledge based personality recognition from text. MICAI 2013, Mexico City, Mexico, Springer LNAI.

  32. S. Poria, A. Gelbukh, A. Hussain, S. Bandyopadhyay and N. Howard. Music genre classification: A semisupervised approach. MICAI 2013, Mexico City, Mexico, Springer LNAI.

  33. S. Poria, A. Gelbukh, D. Das, S. Bandyopadhyay. Fuzzy Clustering for Semi-Supervised Learning—Case study: Construction of an Emotion Lexicon. MICAI 2012. Mexico City, Mexico, Springer LNCS. Best student paper award.

  34. S. Poria, A. Gelbukh, E. Cambria, D. Das, S. Bandyopadhyay. Enriching SenticNet Polarity Scores through Semi-Supervised Fuzzy Clustering. SENTIRE 2012 at IEEE ICDMW 2012. Belgium.

  35. P. Pakray, S. Pal, S. Poria, S. Bandyopadhyay, A. Gelbukh. SMSFR: SMS-Based FAQ Retrieval System. MICAI 2012. Mexico City, Mexico, Springer LNCS.

  36. S. Poria, A. Gelbukh, E. Cambria, A. Hussain, T. Durrani. Merging Senticnet And WordnetAffect Emotion Lists For Sentiment Analysis. IEEE ICSP 2012. China.

  37. D. Das, S. Poria, S. Bandopadhyay. A Classifier Based Approach of Emotion Lexicon Generation, NLDB 2012, The Netherlands, Springer LNCS.

  38. D. Das, S. Poria, S. Bandopadhyay. Building Resources for Multilingual Affect Analysis, A Case Study on Hindi, Bengali and Telugu. ES3 at LREC 2012. Turkey.

  39. P. Pakray, S. Pal, S. Poria, S. Bandyopadhyay. JU CSE TAC: Textual Entailment Recognition System at TAC RTE-7. System report. Recognizing Textual Entailment Track (TAC RTE) at TAC 2011, Text Analysis Conference. USA.

  40. P. Pakray, S. Pal, S. Poria, S. Bandyopadhyay. JU CSE TAC: Textual Entailment Recognition System at TAC RTE-6. System report. Recognizing Textual Entailment Track (TAC RTE) at TAC 2010, Text Analysis Conference. USA.