Related papers: Mapping Visual Themes among Authentic and Coordinated Memes

Mapping Visual Themes among Authentic and Coordinated Memes

URL: http://arxiv.org/abs/2206.02306v1
Date: Mon, 6 Jun 2022 01:26:39 GMT
Title: Mapping Visual Themes among Authentic and Coordinated Memes
Authors: Keng-Chi Chang
Abstract summary: I learn low-dimensional visual embeddings of memes and apply K-means to jointly cluster authentic and coordinated memes. I find that authentic and coordinated memes share a large fraction of visual themes but with varying degrees. A simple logistic regression on the low-dimensional embeddings can discern IRA memes from Reddit memes with an out-sample testing accuracy of 0.84.
Score: 0.0
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: What distinguishes authentic memes from those created by state actors? I utilize a self-supervised vision model, DeepCluster (Caron et al. 2019), to learn low-dimensional visual embeddings of memes and apply K-means to jointly cluster authentic and coordinated memes without additional inputs. I find that authentic and coordinated memes share a large fraction of visual themes but with varying degrees. Coordinated memes from Russian IRA accounts promote more themes around celebrities, quotes, screenshots, military, and gender. Authentic Reddit memes include more themes with comics and movie characters. A simple logistic regression on the low-dimensional embeddings can discern IRA memes from Reddit memes with an out-sample testing accuracy of 0.84.

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