Measuring online service availability using twitter

Authors:
Marti Motoyama;Brendan Meeder;Kirill Levchenko;Geoffrey M. Voelker;Stefan Savage
Affiliations:
Dept. of Computer Science and Engineering, University of California, San Diego;Dept. of Computer Science, Carnegie Mellon University, Pittsburgh;Dept. of Computer Science and Engineering, University of California, San Diego;Dept. of Computer Science and Engineering, University of California, San Diego;Dept. of Computer Science and Engineering, University of California, San Diego
Venue:
WOSN'10 Proceedings of the 3rd conference on Online social networks
Year:
2010

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Abstract

Real-time micro-blogging services such as Twitter are widely recognized for their social dynamics--how they both encapsulate a social graph and propagate information across it. However, the content of this information is equally interesting since it frequently reflects individual experiences with a broad variety of real-time events. Indeed, events of broad interest are commonly revealed in correlated spikes of semantically-related posting activity. In this paper, we explore one such application this of phenomenon: using Twitter data to infer on-line Internet service availability. We show that simple techniques are sufficient to extract key semantic content from "tweets" (i.e., service X is down) and also filter out extraneous noise. We demonstrate the efficacy of this approach at identifying a range of large-scale service outages in 2009 for popular services such as Gmail, Bing and PayPal.