INF-UFG at FiQA 2018 Task 1

Author:

de França Costa Dayan1,da Silva Nadia Felix Felipe1

Affiliation:

1. Federal University of Goias, Goiânia, Brazil

Publisher

ACM Press

Reference33 articles.

1. Sitaram Asur and Bernardo A. Huberman. 2010. Predicting the Future with Social Media. In Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 (WI-IAT '10). IEEE Computer Society, Washington, DC, USA, 492--499. https://doi.org/10.1109/ WI-IAT.2010.63

2. Johan Bollen, Huina Mao, and Xiao-Jun Zeng. 2010. Twitter mood predicts the stock market. CoRR abs/1010.3003 (2010). arXiv:1010.3003. http://arxiv.org/abs/1010.3003

3. Tobias Cabanski, Julia Romberg, and Stefan Conrad. 2017. HHU at SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Data using Machine Learning Methods. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017). Association for Computational Linguistics, Vancouver, Canada, 832--836. http://www.aclweb.org/anthology/S17--2141

4. Keith Cortis, André Freitas, Tobias Daudert, Manuela Huerlimann, Manel Zarrouk, Siegfried Handschuh, and Brian Davis. 2017. SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017). Association for Computational Linguistics, 519--535. https://doi.org/10.18653/v1/S17--2089

5. Orphee De Clercq, Marjan Van de Kauter, Els Lefever, and Veronique Hoste. 2015. LT3: Applying Hybrid Terminology Extraction to Aspect-Based Sentiment Analysis. In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015). Association for Computational Linguistics, Denver, Colorado, 719--724. http://www.aclweb.org/anthology/S15--2122

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