%0 Conference Proceedings
%T A Deep Multi-modal Neural Network for the Identification of Hate Speech from Social Media
%+ National Institute of Technology [Patna] (NIT)
%+ Siksha ’O’ Anusandhan (SOA)
%A Kumar, Gunjan
%A Singh, Jyoti, Prakash
%A Kumar, Abhinav
%Z Part 11: Social Media and Analytics
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 20th Conference on e-Business, e-Services and e-Society (I3E)
%C Galway, Ireland
%Y Denis Dennehy
%Y Anastasia Griva
%Y Nancy Pouloudi
%Y Yogesh K. Dwivedi
%Y Ilias Pappas
%Y Matti Mäntymäki
%I Springer International Publishing
%3 Responsible AI and Analytics for an Ethical and Inclusive Digitized Society
%V LNCS-12896
%P 670-680
%8 2021-09-01
%D 2021
%R 10.1007/978-3-030-85447-8_55
%K Hate-speech
%K Multi-modal
%K Twitter images
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X Hate speech can be particularized as an intentional and chronic act to harm a single person or a group of individuals. This act can be performed via social networking websites such as Twitter, YouTube, Facebook, and more. Most of the existing approaches for finding hate speech are concentrated on either textual or visual information of the posted social media contents. In this work, a multi-modal system is proposed that uses textual as well as the visual contents of the social media post to classify it into Racist, Sexist, Homophobic, Religion-based hate, Other hate and No hate classes. The proposed multi-modal system uses a convolutional neural network-based model to process text and a pre-trained VGG-16 network to process imagery contents. The performance of the proposed model is tested with the benchmark dataset and it achieved significant performance in classifying social media posts into six different hate classes.
%G English
%Z TC 6
%Z WG 6.11
%2 https://inria.hal.science/hal-03648143/document
%2 https://inria.hal.science/hal-03648143/file/512902_1_En_55_Chapter.pdf
%L hal-03648143
%U https://inria.hal.science/hal-03648143
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC6
%~ IFIP-WG6-11
%~ IFIP-I3E
%~ IFIP-LNCS-12896