LT3 at SemEval-2021 Task 6 : using multi-modal compact bilinear pooling to combine visual and textual understanding in memes

Publication type
C1
Publication status
Published
Authors
Singh, P., & Lefever, E.
Editor
Alexis Palmer, Nathan Schneider, Natalie Schluter, Guy Emerson, Aurelie Herbelot and Xiaodan Zhu
Series
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Pagination
1051-1055
Publisher
Association for Computational Linguistics (ACL) (Bangkok, Thailand)
Conference
15th International Workshop on Semantic Evaluation (SemEval-2021) (Bangkok, Thailand)
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Abstract

Internet memes have become ubiquitous in social media networks today. Due to their popularity, they are also a widely used mode of expression to spread disinformation online. As memes consist of a mixture of text and image, they require a multi-modal approach for automatic analysis. In this paper, we describe our contribution to the SemEval-2021 Detection of Persuasian Techniques in Texts and Images Task. We propose a Multi-Modal learning system, which incorporates “memebeddings”, viz. joint text and vision features by combining them with compact bilinear pooling, to automatically identify rhetorical and psychological disinformation techniques. The experimental results show that the proposed system constantly outperforms the competition’s baseline, and achieves the 2nd best Macro F1-score and 14th best Micro F1-score out of all participants.