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Main Authors: Păiş, Vasile, Niţă, Sara, Jerpelea, Alexandru-Iulius, Pană, Luca, Curea, Eric
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.15497
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author Păiş, Vasile
Niţă, Sara
Jerpelea, Alexandru-Iulius
Pană, Luca
Curea, Eric
author_facet Păiş, Vasile
Niţă, Sara
Jerpelea, Alexandru-Iulius
Pană, Luca
Curea, Eric
contents Memes are becoming increasingly more popular in online media, especially in social networks. They usually combine graphical representations (images, drawings, animations or video) with text to convey powerful messages. In order to extract, process and understand the messages, AI applications need to employ multimodal algorithms. In this paper, we introduce a curated dataset of real memes in the Romanian language, with multiple annotation levels. Baseline algorithms were employed to demonstrate the usability of the dataset. Results indicate that further research is needed to improve the processing capabilities of AI tools when faced with Internet memes.
format Preprint
id arxiv_https___arxiv_org_abs_2410_15497
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle RoMemes: A multimodal meme corpus for the Romanian language
Păiş, Vasile
Niţă, Sara
Jerpelea, Alexandru-Iulius
Pană, Luca
Curea, Eric
Computation and Language
Memes are becoming increasingly more popular in online media, especially in social networks. They usually combine graphical representations (images, drawings, animations or video) with text to convey powerful messages. In order to extract, process and understand the messages, AI applications need to employ multimodal algorithms. In this paper, we introduce a curated dataset of real memes in the Romanian language, with multiple annotation levels. Baseline algorithms were employed to demonstrate the usability of the dataset. Results indicate that further research is needed to improve the processing capabilities of AI tools when faced with Internet memes.
title RoMemes: A multimodal meme corpus for the Romanian language
topic Computation and Language
url https://arxiv.org/abs/2410.15497