Automatic Discovery of Political Meme Genres with Diverse Appearances

Abstract

Forms of human communication are not static --- we expect some evolution in the way information is conveyed over time because of advances in technology. One example of this phenomenon is the image-based meme, which has emerged as a dominant form of political messaging in the past decade. While originally used to spread jokes on social media, memes are now having an outsized impact on public perception of world events. A significant challenge in automatic meme analysis has been the development of a strategy to match memes from within a single genre when the appearances of the images vary. Such variation is especially common in memes exhibiting mimicry. For example, when voters perform a common hand gesture to signal their support for a candidate. In this paper we introduce a scalable automated visual recognition pipeline for discovering political meme genres of diverse appearance. This pipeline can ingest meme images from a social network, apply computer vision-based techniques to extract local features and index new images into a database, and then organize the memes into related genres. To validate this approach, we perform a large case study on the 2019 Indonesian Presidential Election using a new dataset of over two million images collected from Twitter and Instagram. Results show that this approach can discover new meme genres with visually diverse images that share common stylistic elements, paving the way forward for further work in semantic analysis and content attribution.

The contingent macro

“…Giorgi (2021), following an assessment of the literature on memes, proposes to identify memes based on three features: irony, manipulation, and intertextuality. Research on memes also witnessed a rising trend in studies employing computational techniques for the automated recognition and classification of memetic instances (Miliani et al, 2020;Bucur et al, 2022;Theisen et al, 2021). Here, too, memes are identified and sorted depending on the presence of characteristics, like multimodality or recurrent layouts.…”

Folk Models of Misinformation on Social Media

“…providing users verifiable corrections of the falsehoods from credible sources to break the illusion of truth [30,93]. An algorithmic is also available for the mainstream social media platforms (the alternative ones do not deem misinformation as a problem [107]) that leverages natural language processing, image analysis, or metadata to detect trolling and memes [50,51,122]. Platforms also have the option for algorithmic "soft" moderation by either obscuring trolling and memes with warnings covers or attaching warning labels [108,125] and "hard" moderation for removing or suspending misinformer accounts [63].…”

Propaganda and Political Memes on Social Media in the 2019 Indonesian Presidential Election

“…Even though it is extraordinary, Williams (2016) mentions that memes have stolen attention in the context of world politics, which indicates that the media of political communication is not static. A meme is an evolutionary form of political communication media, which has taken a dominant place over the last decade (Theisen et al, 2020).…”