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            <title>Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text</title>
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            <namePart type="given">Ali</namePart>
            <namePart type="family">Hürriyetoğlu</namePart>
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    <abstract>Hate speech has emerged as a pressing issue on social media platforms, fueled by the increasing availability of multimodal data and easy internet access. Addressing this problem requires collaborative efforts from researchers, policymakers, and online platforms. In this study, we investigate the detection of hate speech in multimodal data, comprising text-embedded images, by employing advanced deep learning models. The main objective is to identify effective strategies for hate speech detection and content moderation. We conducted experiments using four state-of-the-art classifiers: XLM-Roberta-base, BiLSTM, XLNet base cased, and ALBERT, on the CrisisHateMM[4] dataset, consisting of over 4700 text-embedded images related to the Russia-Ukraine conflict. The best findings reveal that XLM-Roberta-base exhibits superior performance, outperforming other classifiers across all evaluation metrics, including an impressive F1 score of 84.62 for sub-task 1 and 69.73 for sub-task 2. The future scope of this study lies in exploring multimodal approaches to enhance hate speech detection accuracy, integrating ethical considerations to address potential biases, promoting fairness, and safeguarding user rights. Additionally, leveraging larger and more diverse datasets will contribute to developing more robust and generalised hate speech detection solutions.</abstract>
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%0 Conference Proceedings
%T IIC_Team@Multimodal Hate Speech Event Detection 2023: Detection of Hate Speech and Targets using Xlm-Roberta-base
%A Singh, Karanpreet
%A Vajrobol, Vajratiya
%A Aggarwal, Nitisha
%Y Hürriyetoğlu, Ali
%Y Tanev, Hristo
%Y Zavarella, Vanni
%Y Yeniterzi, Reyyan
%Y Yörük, Erdem
%Y Slavcheva, Milena
%S Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F singh-etal-2023-iic
%X Hate speech has emerged as a pressing issue on social media platforms, fueled by the increasing availability of multimodal data and easy internet access. Addressing this problem requires collaborative efforts from researchers, policymakers, and online platforms. In this study, we investigate the detection of hate speech in multimodal data, comprising text-embedded images, by employing advanced deep learning models. The main objective is to identify effective strategies for hate speech detection and content moderation. We conducted experiments using four state-of-the-art classifiers: XLM-Roberta-base, BiLSTM, XLNet base cased, and ALBERT, on the CrisisHateMM[4] dataset, consisting of over 4700 text-embedded images related to the Russia-Ukraine conflict. The best findings reveal that XLM-Roberta-base exhibits superior performance, outperforming other classifiers across all evaluation metrics, including an impressive F1 score of 84.62 for sub-task 1 and 69.73 for sub-task 2. The future scope of this study lies in exploring multimodal approaches to enhance hate speech detection accuracy, integrating ethical considerations to address potential biases, promoting fairness, and safeguarding user rights. Additionally, leveraging larger and more diverse datasets will contribute to developing more robust and generalised hate speech detection solutions.
%U https://aclanthology.org/2023.case-1.18
%P 136-143

Markdown (Informal)

[IIC_Team@Multimodal Hate Speech Event Detection 2023: Detection of Hate Speech and Targets using Xlm-Roberta-base](https://aclanthology.org/2023.case-1.18) (Singh et al., CASE-WS 2023)

• IIC_Team@Multimodal Hate Speech Event Detection 2023: Detection of Hate Speech and Targets using Xlm-Roberta-base (Singh et al., CASE-WS 2023)

ACL

• Karanpreet Singh, Vajratiya Vajrobol, and Nitisha Aggarwal. 2023. IIC_Team@Multimodal Hate Speech Event Detection 2023: Detection of Hate Speech and Targets using Xlm-Roberta-base. In Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text, pages 136–143, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.