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Sifting signal from noise: A new perspective on the meaning of tweets about the "big game"
Journal article   Peer reviewed

Sifting signal from noise: A new perspective on the meaning of tweets about the "big game"

Ian Graves, Nora McDonald and Sean P. Goggins
New media & society, v 18(2), pp 293-312
01 Feb 2016
DOI: https://doi.org/10.1177/1461444814541783
Featured in Collection :   UN Sustainable Development Goals @ Drexel

Abstract

Communication Social Sciences
A good deal of Twitter research focuses on event-detection using algorithms that rely on keywords and tweet density. We present an alternative analysis of tweets, filtering by hashtags related to the 2012 Superbowl and validated against the 2013 baseball World Series. We analyze low-volume, topically similar tweets which reference specific plays (sub-contexts) within the game at the time they occur. These communications are not explicitly linked; they pivot on keywords and do not correlate with spikes in tweets-per-minute. Such phenomena are not readily identified by current event-detection algorithms, which rely on volume to drive the analytic engine. We propose to demonstrate the effectiveness of empirically and theoretically informed approaches and use qualitative analysis and theory to inform the design of future event-detection algorithms. Specifically, we propose theories of Information Grounds and third places to explain sub-contexts that emerge. Conceptualizing sub-contexts as a socio-technical place advances the framing of Twitter event-detection from principally computational to deeply contextual.

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7 Record Views
6 citations in Web of Science
8 citations in Scopus

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Collaboration types
Domestic collaboration
Web of Science research areas
Communication
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