Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Mathew, Binny"'
Autor:
Verma, Gaurav, Grover, Rynaa, Zhou, Jiawei, Mathew, Binny, Kraemer, Jordan, De Choudhury, Munmun, Kumar, Srijan
Violence-provoking speech -- speech that implicitly or explicitly promotes violence against the members of the targeted community, contributed to a massive surge in anti-Asian crimes during the pandemic. While previous works have characterized and bu
Externí odkaz:
http://arxiv.org/abs/2407.15227
Recently, influence functions present an apparatus for achieving explainability for deep neural models by quantifying the perturbation of individual train instances that might impact a test prediction. Our objectives in this paper are twofold. First
Externí odkaz:
http://arxiv.org/abs/2402.14702
Hate speech has become one of the most significant issues in modern society, having implications in both the online and the offline world. Due to this, hate speech research has recently gained a lot of traction. However, most of the work has primaril
Externí odkaz:
http://arxiv.org/abs/2305.03915
Autor:
Saha, Punyajoy, Garimella, Kiran, Kalyan, Narla Komal, Pandey, Saurabh Kumar, Meher, Pauras Mangesh, Mathew, Binny, Mukherjee, Animesh
Recently, social media platforms are heavily moderated to prevent the spread of online hate speech, which is usually fertile in toxic words and is directed toward an individual or a community. Owing to such heavy moderation, newer and more subtle tec
Externí odkaz:
http://arxiv.org/abs/2303.10311
Autor:
Aggarwal, Piush, Chawla, Pranit, Das, Mithun, Saha, Punyajoy, Mathew, Binny, Zesch, Torsten, Mukherjee, Animesh
Exploiting social media to spread hate has tremendously increased over the years. Lately, multi-modal hateful content such as memes has drawn relatively more traction than uni-modal content. Moreover, the availability of implicit content payloads mak
Externí odkaz:
http://arxiv.org/abs/2302.05703
Abusive language is a concerning problem in online social media. Past research on detecting abusive language covers different platforms, languages, demographies, etc. However, models trained using these datasets do not perform well in cross-domain ev
Externí odkaz:
http://arxiv.org/abs/2211.17046
Recently, many studies have tried to create generation models to assist counter speakers by providing counterspeech suggestions for combating the explosive proliferation of online hate. However, since these suggestions are from a vanilla generation m
Externí odkaz:
http://arxiv.org/abs/2205.04304
Due to the sheer volume of online hate, the AI and NLP communities have started building models to detect such hateful content. Recently, multilingual hate is a major emerging challenge for automated detection where code-mixing or more than one langu
Externí odkaz:
http://arxiv.org/abs/2205.00328
Hate speech is regarded as one of the crucial issues plaguing the online social media. The current literature on hate speech detection leverages primarily the textual content to find hateful posts and subsequently identify hateful users. However, thi
Externí odkaz:
http://arxiv.org/abs/2108.00524
WhatsApp is the most popular messaging app in the world. Due to its popularity, WhatsApp has become a powerful and cheap tool for political campaigning being widely used during the 2019 Indian general election, where it was used to connect to the vot
Externí odkaz:
http://arxiv.org/abs/2102.03870