Alejandro Mosquera


2020

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Amsqr at SemEval-2020 Task 12: Offensive Language Detection Using Neural Networks and Anti-adversarial Features
Alejandro Mosquera
Proceedings of the Fourteenth Workshop on Semantic Evaluation

This paper describes a method and system to solve the problem of detecting offensive language in social media using anti-adversarial features. Our submission to the SemEval-2020 task 12 challenge was generated by an stacked ensemble of neural networks fine-tuned on the OLID dataset and additional external sources. For Task-A (English), text normalisation filters were applied at both graphical and lexical level. The normalisation step effectively mitigates not only the natural presence of lexical variants but also intentional attempts to bypass moderation by introducing out of vocabulary words. Our approach provides strong F1 scores for both 2020 (0.9134) and 2019 (0.8258) challenges.

2014

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Mining Lexical Variants from Microblogs: An Unsupervised Multilingual Approach
Alejandro Mosquera | Paloma Moreda Pozo
Proceedings of the 5th Workshop on Language Analysis for Social Media (LASM)

2013

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Improving Web 2.0 Opinion Mining Systems Using Text Normalisation Techniques
Alejandro Mosquera | Paloma Moreda Pozo
Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013

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UMCC_DLSI-(SA): Using a ranking algorithm and informal features to solve Sentiment Analysis in Twitter
Yoan Gutiérrez | Andy González | Roger Pérez | José I. Abreu | Antonio Fernández Orquín | Alejandro Mosquera | Andrés Montoyo | Rafael Muñoz | Franc Camara
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)

2011

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The Use of Metrics for Measuring Informality Levels in Web 2.0 Texts
Alejandro Mosquera | Paloma Moreda
Proceedings of the 8th Brazilian Symposium in Information and Human Language Technology