Abstract

Internet memes have emerged as a novel format for communication and expressing ideas on the web. Their fluidity and creative nature are reflected in their widespread use, often across platforms and occasionally for unethical or harmful purposes. While computational work has already analyzed their high-level virality over time and developed specialized classifiers for hate speech detection, there have been no efforts to date that aim to holistically track, identify, and map internet memes posted on social media. To bridge this gap, we investigate whether internet memes across social media platforms can be contextualized by using a semantic repository of knowledge, namely, a knowledge graph. We collect thousands of potential internet meme posts from two social media platforms, namely Reddit and Discord, and develop an extract-transform-load procedure to create a data lake with candidate meme posts. By …

Metadata

publication

In the Companion Proceedings of The Web Conference 2024 Best Paper Award …, 2024

year

2024

publication date

2024

authors

Saurav Joshi, Filip Ilievski, Luca Luceri

link

https://dl.acm.org/doi/abs/10.1145/3589335.3651970

resource_link

https://arxiv.org/pdf/2311.11157

journal

In the Companion Proceedings of The Web Conference 2024 Best Paper AwardBest Presentation Award