Detection of Propaganda Techniques in Visuo-Lingual Metaphor in Memes
This addresses the challenge of identifying manipulative content in memes on social media, which is an incremental improvement in multimodal propaganda detection.
The paper tackles the problem of detecting propaganda techniques in internet memes by proposing a multimodal deep learning fusion system that combines text and image features, achieving better performance than models using only single modalities.
The exponential rise of social media networks has allowed the production, distribution, and consumption of data at a phenomenal rate. Moreover, the social media revolution has brought a unique phenomenon to social media platforms called Internet memes. Internet memes are one of the most popular contents used on social media, and they can be in the form of images with a witty, catchy, or satirical text description. In this paper, we are dealing with propaganda that is often seen in Internet memes in recent times. Propaganda is communication, which frequently includes psychological and rhetorical techniques to manipulate or influence an audience to act or respond as the propagandist wants. To detect propaganda in Internet memes, we propose a multimodal deep learning fusion system that fuses the text and image feature representations and outperforms individual models based solely on either text or image modalities.