CSECU-DSG at SemEval-2021 Task 6: Orchestrating Multimodal Neural Architectures for Identifying Persuasion Techniques in Texts and Images

Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 1088–1095 Bangkok, Thailand (online), August 5–6, 2021. ©2021 Association for Computational Linguistics 1088 CSECU-DSG at SemEval-2021 Task 6: Orchestrating Multimodal Neural Architectures for Identifying Persuasion Techniques in Texts and Images Tashin Hossain, Jannatun Naim, Fareen Tasneem, Radiathun Tasnia, and Abu Nowshed Chy Department of Computer Science and Engineering University of Chittagong, Chattogram-4331, Bangladesh {tashin.hossain.cu,jannatun.naim.cu,fareen.tasneem, radia.tasnia.cu}@gmail.com and nowshed@cu.ac.bd Abstract Inscribing persuasion techniques in memes is the most impactful way to influence peoples’ mindsets. People are more inclined to memes as they are more stimulating and convincing and hence memes are often exploited by tact- fully engraving propaganda in its context with the intent of attaining specific agenda. This paper describes our participation in the three subtasks featured by SemEval 2021 task 6 on the detection of persuasion techniques in texts and images. We utilize a fusion of logistic re- gression, decision tree, and fine-tuned Distil- BERT for tackling subtask 1. As for subtask 2, we propose a system that consolidates a span identification model and a multi-label classifi- cation model based on pre-trained BERT. We address the multi-modal multi-label classifica- tion of memes defined in subtask 3 by uti- lizing a ResNet50 based image model, Distil- BERT based text model, and a multi-modal ar- chitecture based on multikernel CNN+LSTM and MLP model. The outcomes illustrated the competitive performance of our systems. Keywords: persuasion techniques, transfer learn- ing, multimodal neural architecture. 1 Introduction Persuasion techniques are quite recurrent in so- cial media contents as it reaches a vast community. Proselytizing contents are adroitly implanted in posts and blogs which influence people’s thoughts unconsciously. Nowadays such techniques are also being instilled in memes as people’s attention is easily captured through illustration rather than nar- ration. Manipulators often use this as a tool to promote their own deceitful agenda which can be political or anything else. Fake news is also spread through these disguised duplicitous contents which The first four authors have equal contributions. cause a lot of casualties. Therefore, it is an indis- pensable task to detect these techniques in multi- modal contents to protect the users from deception. The objective of SemEval 2021 task 6 (Dimitrov et al., 2021) is to detect the persuasion techniques in textual and multi-modal contents. This task in- cludes three subtasks where the first two are based on textual contents only. More precisely, the first subtask requires us to detect which persuasion tech- niques among the given 20 techniques are inscribed in the textual content whereas the second subtask requires us to not only find which techniques are used but also to find the specific span of the text each technique corresponds to. The third subtask is a multi-modal multi-label classification problem where we need to identify which of the given 22 techniques are engraved both in the textual and vi- sual content of the meme. An example from the provided dataset along with the desired output for three subtasks is depicted in Figure 1. Numerous …

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