SAJA at TRAC 2020 Shared Task: Transfer Learning for Aggressive Identification with XGBoost

摘要

This paper describes the participation of the SAJA team to the TRAC 2020 shared task on aggressive identification in the English text, we have developed a system based on transfer learning technique depending on universal sentence encoder (USE) embedding that will be trained in our developed model using xgboost classifier to identify the aggressive text data from English content. A reference dataset has been provided from TRAC 2020 to evaluate the developed approach. The developed approach achieved in sub-task EN-A 60.75% Fl (weighted) which ranked fourteenth out of sixteen teams and achieved 85.66% Fl (weighted) in sub-task EN-B which ranked six out of fifteen teams.