CrisisHateMM: Multimodal Analysis of Directed and Undirected Hate Speech in Text-Embedded Images From Russia-Ukraine Conflict

Aashish Bhandari, Siddhant B Shah, Surendrabikram Thapa, Usman Naseem, Mehwish Nasim

Research output: Chapter in Book/Conference paperConference paperpeer-review

2 Citations (Scopus)

Abstract

Text-embedded images are frequently used on social media to convey opinions and emotions, but they can also be a medium for disseminating hate speech, propaganda, and extremist ideologies. During the Russia-Ukraine war, both sides used text-embedded images extensively to spread propaganda and hate speech. To aid in moderating such content, this paper introduces CrisisHateMM, a novel multimodal dataset of over 4,700 text-embedded images from the Russia-Ukraine conflict, annotated for hate and non-hate speech. The hate speech is annotated for directed and undirected hate speech, with directed hate speech further annotated for individual, community, and organizational targets. We benchmark the dataset using unimodal and multimodal algorithms, providing insights into the effectiveness of different approaches for detecting hate speech in text-embedded images. Our results show that multimodal approaches outperform unimodal approaches in detecting hate speech, highlighting the importance of combining visual and textual features. This work provides a valuable resource for researchers and practitioners in automated content moderation and social media analysis. The CrisisHateMM dataset and codes are made publicly available at https://github.com/aabhandari/CrisisHateMM.
Original languageEnglish
Title of host publicationProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1994-2003
Number of pages10
ISBN (Electronic)979-8-3503-0249-3
ISBN (Print)979-8-3503-0250-9
DOIs
Publication statusPublished - 14 Aug 2023
EventThe IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023 - Vancouver Convention Center, Vancouver, Canada
Duration: 18 Jun 202322 Jun 2023

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2023-June
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

ConferenceThe IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023
Abbreviated titleCVPR 2023
Country/TerritoryCanada
CityVancouver
Period18/06/2322/06/23

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