| Automatic sarcasm detection: A survey A Joshi, P Bhattacharyya, MJ Carman ACM Computing Surveys (CSUR) 50 (5), 1-22, 2017 | 416 | 2017 |
| Harnessing context incongruity for sarcasm detection A Joshi, V Sharma, P Bhattacharyya Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015 | 325 | 2015 |
| The iit bombay english-hindi parallel corpus A Kunchukuttan, P Mehta, P Bhattacharyya arXiv preprint arXiv:1710.02855, 2017 | 241 | 2017 |
| Interlingua-based English–Hindi machine translation and language divergence S Dave, J Parikh, P Bhattacharyya Machine Translation 16, 251-304, 2001 | 221 | 2001 |
| A fall-back strategy for sentiment analysis in hindi: a case study A Joshi, AR Balamurali, P Bhattacharyya Proceedings of the 8th ICON, 2010 | 206 | 2010 |
| Feature selection and ensemble construction: A two-step method for aspect based sentiment analysis MS Akhtar, D Gupta, A Ekbal, P Bhattacharyya Knowledge-Based Systems 125, 116-135, 2017 | 196 | 2017 |
| Are word embedding-based features useful for sarcasm detection? A Joshi, V Tripathi, K Patel, P Bhattacharyya, M Carman arXiv preprint arXiv:1610.00883, 2016 | 175 | 2016 |
| Multi-task learning for multi-modal emotion recognition and sentiment analysis MS Akhtar, DS Chauhan, D Ghosal, S Poria, A Ekbal, P Bhattacharyya arXiv preprint arXiv:1905.05812, 2019 | 168 | 2019 |
| An experience in building the indo wordnet-a wordnet for hindi D Narayan, D Chakrabarti, P Pande, P Bhattacharyya First international conference on global WordNet, Mysore, India 24, 2002 | 166 | 2002 |
| Relation extraction: A survey S Pawar, GK Palshikar, P Bhattacharyya arXiv preprint arXiv:1712.05191, 2017 | 163 | 2017 |
| Feature specific sentiment analysis for product reviews S Mukherjee, P Bhattacharyya International conference on intelligent text processing and computational …, 2012 | 157 | 2012 |
| Contextual inter-modal attention for multi-modal sentiment analysis D Ghosal, MS Akhtar, D Chauhan, S Poria, A Ekbal, P Bhattacharyya proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 156 | 2018 |
| Sentiment analysis in twitter with lightweight discourse analysis S Mukherjee, P Bhattacharyya Proceedings of COLING 2012, 1847-1864, 2012 | 144 | 2012 |
| Extracting decision trees from trained neural networks R Krishnan, G Sivakumar, P Bhattacharya Pattern recognition 32 (12), 1999 | 137 | 1999 |
| A hybrid deep learning architecture for sentiment analysis MS Akhtar, A Kumar, A Ekbal, P Bhattacharyya Proceedings of COLING 2016, the 26th International Conference on …, 2016 | 130 | 2016 |
| Simple syntactic and morphological processing can help English-Hindi statistical machine translation A Ramanathan, J Hegde, R Shah, P Bhattacharyya, M Sasikumar Proceedings of the Third International Joint Conference on Natural Language …, 2008 | 117 | 2008 |
| Is question answering an acquired skill? G Ramakrishnan, S Chakrabarti, D Paranjpe, P Bhattacharya Proceedings of the 13th international conference on World Wide Web, 111-120, 2004 | 112 | 2004 |
| Your sentiment precedes you: Using an author’s historical tweets to predict sarcasm A Khattri, A Joshi, P Bhattacharyya, M Carman Proceedings of the 6th workshop on computational approaches to subjectivity …, 2015 | 110 | 2015 |
| Cross-lingual sentiment analysis for indian languages using linked wordnets AR Balamurali, A Joshi, P Bhattacharyya Proceedings of COLING 2012: Posters, 73-82, 2012 | 106 | 2012 |
| Hindi POS tagger using naive stemming: harnessing morphological information without extensive linguistic knowledge M Shrivastava, P Bhattacharyya International Conference on NLP (ICON08), Pune, India, 2008 | 105 | 2008 |
