| Inf-ufrgs-opinion-mining at semeval-2016 task 6: Automatic generation of a training corpus for unsupervised identification of stance in tweets M Dias, K Becker Proceedings of the 10th International Workshop on Semantic Evaluation …, 2016 | 22 | 2016 |
| Detecção semi-supervisionada de posicionamento em tweets baseada em regras de sentimento. M Dias, K Becker SBBD, 40-51, 2016 | 3 | 2016 |
| Identificação de Candidatos à Fiscalização por Evasão do Tributo ISS M Dias, K Becker | 2 | 2017 |
| INF-UFRGS at SemEval-2017 Task 5: A Supervised Identification of Sentiment Score in Tweets and Headlines T Zini, K Becker, M Dias Proceedings of the 11th International Workshop on Semantic Evaluation …, 2017 | 2 | 2017 |
| An heuristics-based, weakly-supervised approach for classification of stance in tweets M Dias, K Becker 2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI), 73-80, 2016 | 2 | 2016 |
| Combining compact news representations generated using DistilBERT and topological features to classify fake news CAC Sáenz, M Dias, K Becker Anais do VIII Symposium on Knowledge Discovery, Mining and Learning, 209-216, 2020 | | 2020 |
| Detecção não supervisionada de posicionamento em textos de tweets M Dias Universidade Federal do Rio Grande do Sul, 2017 | | 2017 |
Karin BeckerInstituto de Informática, UFRGSE-mail confirmado em inf.ufrgs.br
