Multilingual Detection of Persuasion Techniques in Memes
- DOI
- 10.2991/978-94-6463-740-3_22How to use a DOI?
- Keywords
- Sentiment Analysis; Transformer; Multimodals; BERT; VisualBERT; DVTT; MMBT
- Abstract
Online disinformation efforts employ memes, a highly popular kind of content. They get the most success on social media platforms due to their ability to easily access a large audience. As part of a disinformation campaign, memes use different types of rhetorical and psychological techniques, like slander, insulting grouping, and oversimplifying causes, to get people to do what they want. This research explores the complex field of the multilingual identification of persuasive strategies in memes. Finding persuasion techniques used for sentiment analysis of textual content in memes is the first part of the research. The second part uses binary classification to see if there are persuasion techniques in both the textual and visual parts of memes. The study uses a thorough method to complete these subtasks, which are meant to help people understand and find persuasive elements in memes that are written in different languages.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Alok Ranjan AU - Ishan Papnai AU - Jatin Gupta AU - Mehul Aggarwal AU - Anita Saroj PY - 2025 DA - 2025/06/25 TI - Multilingual Detection of Persuasion Techniques in Memes BT - Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024) PB - Atlantis Press SP - 251 EP - 260 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6463-740-3_22 DO - 10.2991/978-94-6463-740-3_22 ID - Ranjan2025 ER -