The task consists of, given a tweet associated with a violent incident, recognizing the crime category to which it belongs (multi-class classification).
Publication
Luis Joaquín Arellano, Hugo Jair Escalante, Luis Villaseñor-Pineda, Manuel Montes-y-Gómez, Fernando Sanchez-Vega (2022) Overview of DA-VINCIS at IberLEF 2022: Detection of Aggressive and Violent Incidents from Social Media in Spanish. Procesamiento del Lenguaje Natural, Revista nº 69, septiembre de 2022, pp. 207-215
Language
Spanish
NLP topic
Abstract task
Dataset
Year
2022
Publication link
Ranking metric
F1
Task results
| System | Precision | Recall | F1 Sort ascending | CEM | Accuracy | MacroPrecision | MacroRecall | MacroF1 | RMSE | MicroPrecision | MicroRecall | MicroF1 | MAE | MAP | UAS | LAS | MLAS | BLEX | Pearson correlation | Spearman correlation | MeasureC | BERTScore | EMR | Exact Match | F0.5 | Hierarchical F | ICM | MeasureC | Propensity F | Reliability | Sensitivity | Sentiment Graph F1 | WAC | b2 | erde30 | sent | weighted f1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GDUT | 0.5500 | 0.5640 | 0.5540 | ||||||||||||||||||||||||||||||||||
| VICOMTECH | 0.5170 | 0.5450 | 0.5280 | ||||||||||||||||||||||||||||||||||
| ITAINNOVA | 0.5090 | 0.5030 | 0.5040 | ||||||||||||||||||||||||||||||||||
| CIC-IPN | 0.4670 | 0.5200 | 0.4900 | ||||||||||||||||||||||||||||||||||
| CIMAT-UG-UAM-IDIAP | 0.6550 | 0.4210 | 0.4730 |
