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

Gretel Liz De la Peña Sarracén, Paolo Rosso, Anastasia Giachanou


Abstract
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.
Anthology ID:
2020.semeval-1.115
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Editors:
Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
Venue:
SemEval
SIG:
SIGLEX
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
908–915
Language:
URL:
https://aclanthology.org/2020.semeval-1.115
DOI:
10.18653/v1/2020.semeval-1.115
Bibkey:
Cite (ACL):
Gretel Liz De la Peña Sarracén, Paolo Rosso, and Anastasia Giachanou. 2020. PRHLT-UPV at SemEval-2020 Task 8: Study of Multimodal Techniques for Memes Analysis. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 908–915, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
PRHLT-UPV at SemEval-2020 Task 8: Study of Multimodal Techniques for Memes Analysis (De la Peña Sarracén et al., SemEval 2020)
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PDF:
https://aclanthology.org/2020.semeval-1.115.pdf