Finding and exploring memes in social media
Hohyon Ryu, Matthew Lease, Nicholas Woodward · 2012
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.