The increasing use of OSM during emergency, or potentially threatening, situations creates conditions in which emergency planners and responders need a high level of investigative skill to weed through a dynamic information landscape to determine the quality of information to contribute to improved situation awareness. This weeding process transforms the big data environment of OSM to focused information retrieval. Inquiry into indicators of quality in OSM (authority, objectivity, currency, coverage, and glyphicality) during severe weather situations informs how OSM impacts the information behavior of the severe weather enterprise of the U. S. Specifically, this paper focuses on investigation into how a particular element of the severe weather enterprise in the Midwest, the integrated warning team (IWT), identifies relevant information in OSM during severe weather events. This paper describes the theoretical framework of an inquiry into information behavior of the IWT during severe weather events through the lens of cognitive authority theory (Wilson, 1983) and Bonnici’s (2016) CAF-QIS for understanding the phenomena of both credibility and trustworthiness in the Twittersphere where author is potentially unknown.

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