Zobrazeno 1 - 10
of 33
pro vyhledávání: '"ElSherief, Mai"'
Autor:
ElSherief, Mai, Ziems, Caleb, Muchlinski, David, Anupindi, Vaishnavi, Seybolt, Jordyn, De Choudhury, Munmun, Yang, Diyi
Hate speech has grown significantly on social media, causing serious consequences for victims of all demographics. Despite much attention being paid to characterize and detect discriminatory speech, most work has focused on explicit or overt hate spe
Externí odkaz:
http://arxiv.org/abs/2109.05322
Autor:
Alshehri, Azizah A., Elsherief, Mai F., Devecioglu, Dilara, Salama, Mohamed Abdelbaset, Sakr, Hazem, Abdin, Mohamed, El.Fadly, Enas, Kamel, Reham M., Saleh, Mohamed N.
Publikováno v:
In Biocatalysis and Agricultural Biotechnology June 2024 58
Autor:
Elsherief, Mai F., Devecioglu, Dilara, Saleh, Mohamed N., Karbancioglu-Guler, Funda, Capanoglu, Esra
Publikováno v:
In International Journal of Biological Macromolecules April 2024 264 Part 2
Existing work on automated hate speech classification assumes that the dataset is fixed and the classes are pre-defined. However, the amount of data in social media increases every day, and the hot topics changes rapidly, requiring the classifiers to
Externí odkaz:
http://arxiv.org/abs/2106.02821
Autor:
Zannettou, Savvas, ElSherief, Mai, Belding, Elizabeth, Nilizadeh, Shirin, Stringhini, Gianluca
The Web has become the main source for news acquisition. At the same time, news discussion has become more social: users can post comments on news articles or discuss news articles on other platforms like Reddit. These features empower and enable dis
Externí odkaz:
http://arxiv.org/abs/2005.07926
Autor:
Gaut, Andrew, Sun, Tony, Tang, Shirlyn, Huang, Yuxin, Qian, Jing, ElSherief, Mai, Zhao, Jieyu, Mirza, Diba, Belding, Elizabeth, Chang, Kai-Wei, Wang, William Yang
Recent developments in Neural Relation Extraction (NRE) have made significant strides towards Automated Knowledge Base Construction (AKBC). While much attention has been dedicated towards improvements in accuracy, there have been no attempts in the l
Externí odkaz:
http://arxiv.org/abs/1911.03642
Autor:
Sun, Tony, Gaut, Andrew, Tang, Shirlyn, Huang, Yuxin, ElSherief, Mai, Zhao, Jieyu, Mirza, Diba, Belding, Elizabeth, Chang, Kai-Wei, Wang, William Yang
As Natural Language Processing (NLP) and Machine Learning (ML) tools rise in popularity, it becomes increasingly vital to recognize the role they play in shaping societal biases and stereotypes. Although NLP models have shown success in modeling vari
Externí odkaz:
http://arxiv.org/abs/1906.08976
Existing computational models to understand hate speech typically frame the problem as a simple classification task, bypassing the understanding of hate symbols (e.g., 14 words, kigy) and their secret connotations. In this paper, we propose a novel t
Externí odkaz:
http://arxiv.org/abs/1904.02418
Existing work on automated hate speech detection typically focuses on binary classification or on differentiating among a small set of categories. In this paper, we propose a novel method on a fine-grained hate speech classification task, which focus
Externí odkaz:
http://arxiv.org/abs/1809.00088
Publikováno v:
ICWSM 2018
While social media has become an empowering agent to individual voices and freedom of expression, it also facilitates anti-social behaviors including online harassment, cyberbullying, and hate speech. In this paper, we present the first comparative s
Externí odkaz:
http://arxiv.org/abs/1804.04649