Infotec + CentroGEO at SemEval-2020 Task 8: Deep Learning and Text Categorization approach for Memes classification

Guillermo Ruiz, Eric S. Tellez, Daniela Moctezuma, Sabino Miranda-Jiménez, Tania Ramírez-delReal, Mario Graff


Abstract
The information shared on social media is increasingly important; both images and text, and maybe the most popular combination of these two kinds of data are the memes. This manuscript describes our participation in Memotion task at SemEval 2020. This task is about to classify the memes in several categories related to the emotional content of them. For the proposed system construction, we used different strategies, and the best ones were based on deep neural networks and a text categorization algorithm. We obtained results analyzing the text and images separately, and also in combination. Our better performance was achieved in Task A, related to polarity classification.
Anthology ID:
2020.semeval-1.151
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:
1141–1147
Language:
URL:
https://aclanthology.org/2020.semeval-1.151
DOI:
10.18653/v1/2020.semeval-1.151
Bibkey:
Cite (ACL):
Guillermo Ruiz, Eric S. Tellez, Daniela Moctezuma, Sabino Miranda-Jiménez, Tania Ramírez-delReal, and Mario Graff. 2020. Infotec + CentroGEO at SemEval-2020 Task 8: Deep Learning and Text Categorization approach for Memes classification. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1141–1147, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
Infotec + CentroGEO at SemEval-2020 Task 8: Deep Learning and Text Categorization approach for Memes classification (Ruiz et al., SemEval 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.semeval-1.151.pdf