Publications

2018

Amir, S. (2018). Agile Social Media Analysis with Neural Networks. Doctoral Dissertation, Instituto Superior Técnico da Universidade de Lisboa.

2017

Amir, S., Coppersmith, G., Carvalho, P., Silva, M. J., and Wallace, B. C. (2017). Quantifying mental health from social media with neural user embeddings. Journal of Machine Learning Research, W&C Track.

2016

Amir, S., Wallace, B. C., Lyu, H., Carvalho, P., and Silva, M. J. (2016). Modelling context with user embeddings for sarcasm detection in social media. Proceedings of the Conference on Natural Language Learning.

press coverage

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Amir, S., Astudillo, R. F., Ling, W., Silva, M. J., Trancoso, I., and Redol, R. A. (2016). INESC-ID at semeval-2016 task 4-a: Reducing the problem of out-of-embedding words. Proceedings of SemEval, pages 238–242.

2015

Amir, S., Ling, W., Astudillo, R., Martins, B., Silva, M. J., and Trancoso, I. (2015). INESC-ID: A regression model for large scale twitter sentiment lexicon induction. In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pages 613–618, Denver, Colorado.

Astudillo, R., Amir, S., Ling, W., Silva, M., and Trancoso, I. (2015). Learning word representations from scarce and noisy data with embedding subspaces. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1074–1084, Beijing, China.

Astudillo, R., Amir, S., Ling, W., Martins, B., Silva, M. J., and Trancoso, I. (2015). INESC-ID: Sentiment analysis without hand-coded features or linguistic resources using embedding subspaces. In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pages 652–656, Denver, Colorado.

Ling, W., Dyer, C., Black, A. W., Trancoso, I., Fermandez, R., Amir, S., Marujo, L., and Luis, T. (2015). Finding function in form: Compositional character models for open vocabulary word representation. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pages 1520–1530, Lisbon, Portugal.

Ling, W., Tsvetkov, Y., Amir, S., Fermandez, R., Dyer, C., Black, A. W., and Lin, C. C. (2015). Not all contexts are created equal: Better word representations with variable attention. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (pp. 1367-1372).

Saleiro, P., Amir, S., Silva, M., and Soares, C. (2015). POPmine: Tracking political opinion on the web. In 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, pages 1521–1526.

2014

Amir, S., Almeida, M. B., Martins, B., Filgueiras, J. a., and Silva, M. J. (2014). TUGAS: Exploiting unlabelled data for twitter sentiment analysis. In Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), pages 673–677, Dublin, Ireland.

2013

Filgueiras, J. and Amir, S. (2013). POPSTAR at replab 2013: Polarity for reputation classification. In CLEF 2013 Eval. Labs and Workshop Online Working Notes.

Moreira, S., Batista, D. S., Carvalho, P., Couto, F. M., & Silva, M. J. (2013). Tracking politics with POWER. Program, 47(2), 120-135.

Moreira, S., Filgueiras, J., Martins, B., Couto, F., & Silva, M. J. (2013). REACTION: A naive machine learning approach for sentiment classification. In Second Joint Conference on Lexical and Computational Semantics (* SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Vol. 2, pp. 490-494).

2011

Moreira, S., Batista, D., Carvalho, P., Couto, F. M., & Silva, M. J. (2011, June). POWER-Politics Ontology for Web Entity Retrieval. In International Conference on Advanced Information Systems Engineering (pp. 489-500). Springer, Berlin, Heidelberg.