Finding and exploring memes in social media

Abstract

Online critical literacy challenges readers to recognize and question how online textual information has been shaped by its greater context. While comparing information from multiple sources provides a foundation for such awareness, keeping pace with everything being written is a daunting proposition, especially for the casual reader. We propose a new form of technological assistance for critical literacy which automatically discovers and displays underlying memes: ideas represented by similar phrases which occur across diýerent information sources. By surfacing these memes to users, we create a rich hypertext representation in which underlying memes can be explored in context. Given the vast scale of social media, we describe a highly-scalable system architecture designed for MapReduce distributed computing. To validate our approach, we report on use of our system to discover and browse memes in a 1.5 TB collection of crawled social media. Our primary contributions include: 1) a novel technological approach and hypertext browsing design for supporting critical literacy; and 2) a highly-scalable system architecture for meme discovery, providing a solid foundation for further system extensions and refinements.