PRHLT-UPV at SemEval-2020 Task 8: Study of Multimodal Techniques for Memes Analysis

SEMEVAL 2020 · Gretel Liz De la Pe{\~n}a Sarrac{\'e}n, Paolo Rosso, Anastasia Giachanou ·

This paper describes the system submitted by the PRHLT-UPV team for the task 8 of SemEval-2020: Memotion Analysis. We propose a multimodal model that combines pretrained models of the BERT and VGG architectures. The BERT model is used to process the textual information and VGG the images. The multimodal model is used to classify memes according to the presence of offensive, sarcastic, humorous and motivating content. Also, a sentiment analysis of memes is carried out with the proposed model. In the experiments, the model is compared with other approaches to analyze the relevance of the multimodal model. The results show encouraging performances on the final leaderboard of the competition, reaching good positions in the ranking of systems.

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Sentiment Analysis

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Adam • Attention Dropout • BERT • Convolution • Dense Connections • Dropout • GELU • Layer Normalization • Linear Layer • Linear Warmup With Linear Decay • Max Pooling • Multi-Head Attention • ReLU • Residual Connection • Scaled Dot-Product Attention • Softmax • VGG • Weight Decay • WordPiece

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PRHLT-UPV at SemEval-2020 Task 8: Study of Multimodal Techniques for Memes Analysis

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