The tasks consists on classifying tweets about companies to one of the seven standard reputation dimensions of the RepTrak Framework developed by the Reputation Institute. The task can be viewed as a complement to topic detection, as it provides a broad classification of the aspects of the company under public scrutiny.
Publication
Enrique Amigó, Jorge Carrillo de Albornoz, Irina Chugur, Adolfo Corujo, Julio Gonzalo, Edgar Meij, Damiano Spina (2014) Overview of RepLab 2014: Author Profiling and Reputation Dimensions for Online Reputation Management.CEUR Proceedings. http://ceur-ws.org/Vol-1180/#CLEF2014wn-Rep-AmigoEt2014
Language
Spanish
NLP topic
Abstract task
Dataset
Year
2014
Publication link
Task results
| System | Precision | Recall | F1 | CEM | Accuracy Sort ascending | 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| uogTr_RD_4 | 0.7300 | ||||||||||||||||||||||||||||||||||||
| DAE_RD_! | 0.7200 | ||||||||||||||||||||||||||||||||||||
| LyS_RD_1 | 0.7200 | ||||||||||||||||||||||||||||||||||||
| CIRGIRDISCO_RD_3 | 0.7100 | ||||||||||||||||||||||||||||||||||||
| SIBtex_RD_1 | 0.7000 |
