no code implementations • SEMEVAL 2017 • Sara Rosenthal, Noura Farra, Preslav Nakov
This paper describes the fifth year of the Sentiment Analysis in Twitter task.
2 code implementations • SEMEVAL 2019 • Marcos Zampieri, Shervin Malmasi, Preslav Nakov, Sara Rosenthal, Noura Farra, Ritesh Kumar
We present the results and the main findings of SemEval-2019 Task 6 on Identifying and Categorizing Offensive Language in Social Media (OffensEval).
2 code implementations • NAACL 2019 • Marcos Zampieri, Shervin Malmasi, Preslav Nakov, Sara Rosenthal, Noura Farra, Ritesh Kumar
In particular, we model the task hierarchically, identifying the type and the target of offensive messages in social media.
no code implementations • 24 Feb 2019 • Aditi Chaudhary, Siddharth Dalmia, Junjie Hu, Xinjian Li, Austin Matthews, Aldrian Obaja Muis, Naoki Otani, Shruti Rijhwani, Zaid Sheikh, Nidhi Vyas, Xinyi Wang, Jiateng Xie, Ruochen Xu, Chunting Zhou, Peter J. Jansen, Yiming Yang, Lori Levin, Florian Metze, Teruko Mitamura, David R. Mortensen, Graham Neubig, Eduard Hovy, Alan W. black, Jaime Carbonell, Graham V. Horwood, Shabnam Tafreshi, Mona Diab, Efsun S. Kayi, Noura Farra, Kathleen McKeown
This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery and Linking (EDL), and detection of Situation Frames in Text and Speech (SF Text and Speech).
no code implementations • EACL 2017 • Noura Farra, Kathleen McKeown
We consider entity-level sentiment analysis in Arabic, a morphologically rich language with increasing resources.
no code implementations • LREC 2014 • Wajdi Zaghouani, Behrang Mohit, Nizar Habash, Ossama Obeid, Nadi Tomeh, Alla Rozovskaya, Noura Farra, Sarah Alkuhlani, Kemal Oflazer
Finally, we present the annotation tool that was developed as part of this project, the annotation pipeline, and the quality of the resulting annotations.