The Persuasive Memescape: Understanding Effectiveness and Societal Implications of Internet Memes

Abstract

Persuasive meme identification is a crucial task in automatically categorizing memes based on their persuasive nature. Memes, being highly influential in online communication, have the ability to shape individuals' attitudes, behaviors, and beliefs, both positively and negatively. They can be utilized to promote positive actions, challenge social norms, and raise awareness, but they can also perpetuate harmful ideologies, spread misinformation, stereotype, and manipulate emotions. In this paper, we are addressing this challenge by empirically investigating three novel tasks, viz. (i) Task 1: Persuasive meme detection, (ii) Task 2: Identification of the effectiveness of persuasive memes, and (iii) Task 3: Identification of persuasion techniques used in persuasive memes. To this end, we make the very first attempt to release a highquality, large-scale dataset, Persuasive_meme 1 , since there is no publicly available such dataset for the Hindi-English code-mixed (Hinglish) domain. 2 We further developed several baseline unimodal and multimodal models for these tasks. Empirical evaluation with respect to both, qualitative and quantitative analysis, on the Persuasive_meme dataset highlight the significance of multimodality in addressing these tasks effectively. Additionally, we discuss the limitations of the current models and emphasize the need for further research to overcome these challenges.