Bridging gaps in image meme research: A multidisciplinary paradigm for scaling up qualitative analyses

Abstract

This paper outlines a multidisciplinary framework (Digital Rhetorical Ecosystem or DRE3) for scaling up qualitative analyses of image memes. First, we make a case for applying rhetorical theory to examine image memes as quasi‐arguments that promote claims on a variety of political and social issues. Next, we argue for integrating rhetorical analysis of image memes into an ecological framework to trace interaction and evolution of memetic claims as they coalesce into evidence ecosystems that inform public narratives. Finally, we apply a computational framework to address the particular problem of claim identification in memes at large scales. Our integrated framework answers the recent call in information studies to highlight the social, political, and cultural attributes of information phenomena, and bridges the divide between small‐scale qualitative analyses and large‐scale computational analyses of image memes. We present this theoretical framework to guide the development of research questions, processes, and computational architecture to study the widespread and powerful influence of image memes in shaping consequential public beliefs and sentiments.

Topicality boosts popularity: a comparative analysis of NYT articles and Reddit memes

“…By identifying meme topics, in this paper, we connect the individual posts to the broader discourse they are a part of and analyze overall trends in internet discourse across 5 years of data. Our method moves beyond individual posts to analyze the ideas purported by memes, the importance of which is highlighted by Mascarenhas et al (2024).…”