Recent publications
Chapter (peer-reviewed)
Kovatchev, V, Smith, P, Lee, M & Devine, RT 2021, Can vectors read minds better than experts? Comparing data augmentation strategies for the automated scoring of children’s mindreading ability. in C Zong, F Xia, W Li & R Navigli (eds), Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). International Joint Conference on Natural Language Processing (IJCNLP), Association for Computational Linguistics, ACL, The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing , Bangkok, Thailand, 1/08/21. <https://arxiv.org/abs/2106.01635>
Kovatchev, V, Smith, P, Lee, M, Grumley Traynor, I, Luque Aguilera, I & Devine, RT 2020, What is on your mind? Automated scoring of mindreading in childhood and early adolescence. in D Scott, N Bel & C Zong (eds), Proceedings of the 28th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Barcelona, Spain, pp. 6217, International Conference on Computational Linguistics , Barcelona, Spain, 8/12/20. https://doi.org/10.18653/v1/2020.coling-main.547
Smith, P & Lee, M 2012, Cross-discourse Development of Supervised Sentiment Analysis in the Clinical Domain. in Proceedings of the 3rd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis: ACL 2012 Workshop. Association of Computational Linguistics, pp. 79-83. <http://aclweb.org/anthology//W/W12/W12-3712.pdf>
Conference contribution
Kovatchev, V, Smith, P, Lee, M & Devine, R 2021, Can vectors read minds better than experts? Comparing data augmentation strategies for the automated scoring of children's mindreading ability. in C Zong, F Xia, W Li & R Navigli (eds), ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference. vol. 1, Proceedings of the conference - Association for Computational Linguistics. Meeting, Association for Computational Linguistics, ACL, pp. 1196-1206, Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL-IJCNLP 2021, Virtual, Online, 1/08/21. https://doi.org/10.18653/v1/2021.acl-long.96
Alduayj, SS & Smith, P 2019, Sentiment Classification and Prediction of Job Interview Performance. in 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019., 8769559, 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019, Institute of Electrical and Electronics Engineers (IEEE), 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019, Riyadh, Saudi Arabia, 1/05/19. https://doi.org/10.1109/CAIS.2019.8769559
Smith, P & Lee, M 2014, Acknowledging discourse function for sentiment analysis. in A Gelbukh (ed.), Computational Linguistics and Intelligent Text Processing : 15th International Conference, CICLing 2014, Kathmandu, Nepal, April 6-12, 2014, Proceedings, Part II. vol. 8404 LNCS, Lecture Notes in Computer Science , vol. 8404, Springer, pp. 45-52, Computational Linguistics and Intelligent Text Processing, 15th International Conference, CICLing 2014, Kathmandu, Nepal, Nepal, 6/04/14. https://doi.org/10.1007/978-3-642-54903-8-4
Smith, P & Lee, M 2013, A CCG-based approach to fine-grained sentiment analysis in microtext. in Analyzing Microtext - Papers from the AAAI Spring Symposium, Technical Report. vol. SS-13-01, pp. 80-86, 2013 AAAI Spring Symposium, Palo Alto, CA, United States, 25/03/13.
Smith, P & Lee, M 2012, A CCG-Based Approach to Fine-Grained Sentiment Analysis. in Proceedings of the 2nd Workshop on Sentiment Analysis where AI meets Psychology , SAAIP 2012.: COLING 2012 Workshop. Association of Computational Linguistics, pp. 3-16. <http://www.aclweb.org/anthology/W12-5302.pdf>
Preprint
Kovatchev, V, Smith, P, Lee, M & Devine, R 2021 'Can vectors read minds better than experts? Comparing data augmentation strategies for the automated scoring of children's mindreading ability' arXiv. <https://arxiv.org/abs/2106.01635v1>
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