no code implementations • 2 Nov 2019 • Muhammad Abdul-Mageed, Chiyu Zhang, Arun Rajendran, AbdelRahim Elmadany, Michael Przystupa, Lyle Ungar
In this work we exploit a newly-created Arabic dataset with ground truth age and gender labels to learn these attributes both individually and in a multi-task setting at the sentence level.
no code implementations • 31 Oct 2019 • Muhammad Abdul-Mageed, Chiyu Zhang, AbdelRahim Elmadany, Arun Rajendran, Lyle Ungar
Prediction of language varieties and dialects is an important language processing task, with a wide range of applications.
no code implementations • 9 Jun 2019 • Arun Rajendran, Chiyu Zhang, Muhammad Abdul-Mageed
In this paper, we explore various approaches for learning two types of appraisal components from happy language.
no code implementations • 9 Jun 2019 • Arun Rajendran, Chiyu Zhang, Muhammad Abdul-Mageed
We examine learning offensive content on Twitter with limited, imbalanced data.
no code implementations • SEMEVAL 2019 • Chiyu Zhang, Arun Rajendran, Muhammad Abdul-Mageed
We present our deep learning models submitted to the SemEval-2019 Task 4 competition focused at Hyperpartisan News Detection.
no code implementations • SEMEVAL 2019 • Arun Rajendran, Chiyu Zhang, Muhammad Abdul-Mageed
We examine learning offensive content on Twitter with limited, imbalanced data.