Amobee at SemEval-2019 Tasks 5 and 6: Multiple Choice CNN Over Contextual Embedding

Alon Rozental, Dadi Biton


Abstract
This article describes Amobee’s participation in “HatEval: Multilingual detection of hate speech against immigrants and women in Twitter” (task 5) and “OffensEval: Identifying and Categorizing Offensive Language in Social Media” (task 6). The goal of task 5 was to detect hate speech targeted to women and immigrants. The goal of task 6 was to identify and categorized offensive language in social media, and identify offense target. We present a novel type of convolutional neural network called “Multiple Choice CNN” (MC- CNN) that we used over our newly developed contextual embedding, Rozental et al. (2019). For both tasks we used this architecture and achieved 4th place out of 69 participants with an F1 score of 0.53 in task 5, in task 6 achieved 2nd place (out of 75) in Sub-task B - automatic categorization of offense types (our model reached places 18/2/7 out of 103/75/65 for sub-tasks A, B and C respectively in task 6).
Anthology ID:
S19-2066
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Editors:
Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
377–381
Language:
URL:
https://aclanthology.org/S19-2066
DOI:
10.18653/v1/S19-2066
Bibkey:
Cite (ACL):
Alon Rozental and Dadi Biton. 2019. Amobee at SemEval-2019 Tasks 5 and 6: Multiple Choice CNN Over Contextual Embedding. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 377–381, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
Amobee at SemEval-2019 Tasks 5 and 6: Multiple Choice CNN Over Contextual Embedding (Rozental & Biton, SemEval 2019)
Copy Citation:
PDF:
https://aclanthology.org/S19-2066.pdf
Data
HatEval