Detecting and Evaluating Local Text Reuse in Social Networks

Texts propagate among participants in many social networks and provide evidence for network structure. We describe intrinsic and extrinsic evaluations for algorithms that detect clusters of reused passages embedded within longer documents in large collections. We explore applications of these approaches to two case studies: the culture of free reprinting in the nineteenth-century United States and the use of similar language in the public statements of U.S. members of Congress.