International audienceThe massive growth of user-generated web content through blogs, online forums and most notably, social media networks, led to a large spreading of hatred or abusive messages which have to be moderated. This paper proposes a supervised approach to hate speech detection towards immigrants and women in English tweets. Several models have been developed ranging from feature-engineering approaches to neural ones
Social media posts containing hate speech are reproduced and redistributed at an accelerated pace, r...
University of Minnesota M.S. thesis. May 2020. Major: Computer Science. Advisor: Richard Maclin. 1 c...
Detecting harmful content or hate speech on social media is a significant challenge due to the high ...
Due to the massive rise of users in social media, the presence of verbal abuse, hate speech and bull...
Hateful and abusive speech presents a major challenge for all online social media platforms. Recent ...
Hate speech is prevalent in social media platforms. Systems that can automatically detect offensive ...
Social media companies struggle to control the quality of the content on their platforms. The sheer ...
International audienceMultiword expression (MWE) identification in tweets is a complex task due to t...
International audienceHate speech (HS) is legally punished in many countries. Manual moderation of h...
In recent years, the main medium for communication and dissemination of information amongst internet...
This paper addresses the important problem of discerning hateful content in social media. We propose...
Social Media are sensors in the real world that can be used to measure the pulse of societies. Howev...
Hate speech detection on social media platforms is crucial as it helps to avoid severe harm to margi...
The increasing phenomenon of “cyberhate” is concerning because of the potential social implications ...
This paper reports on the systems the InriaFBK Team submitted to the EVALITA 2018-Shared Task on Hat...
Social media posts containing hate speech are reproduced and redistributed at an accelerated pace, r...
University of Minnesota M.S. thesis. May 2020. Major: Computer Science. Advisor: Richard Maclin. 1 c...
Detecting harmful content or hate speech on social media is a significant challenge due to the high ...
Due to the massive rise of users in social media, the presence of verbal abuse, hate speech and bull...
Hateful and abusive speech presents a major challenge for all online social media platforms. Recent ...
Hate speech is prevalent in social media platforms. Systems that can automatically detect offensive ...
Social media companies struggle to control the quality of the content on their platforms. The sheer ...
International audienceMultiword expression (MWE) identification in tweets is a complex task due to t...
International audienceHate speech (HS) is legally punished in many countries. Manual moderation of h...
In recent years, the main medium for communication and dissemination of information amongst internet...
This paper addresses the important problem of discerning hateful content in social media. We propose...
Social Media are sensors in the real world that can be used to measure the pulse of societies. Howev...
Hate speech detection on social media platforms is crucial as it helps to avoid severe harm to margi...
The increasing phenomenon of “cyberhate” is concerning because of the potential social implications ...
This paper reports on the systems the InriaFBK Team submitted to the EVALITA 2018-Shared Task on Hat...
Social media posts containing hate speech are reproduced and redistributed at an accelerated pace, r...
University of Minnesota M.S. thesis. May 2020. Major: Computer Science. Advisor: Richard Maclin. 1 c...
Detecting harmful content or hate speech on social media is a significant challenge due to the high ...