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Abstract

Weather-predictive tasks during high risk severe weather events are carried out for the common good of the community by virtual teams of weather professionals. Severe weather predictors are responsible for producing the early warnings that inform people in harms way and potentially save lives. Should we be concerned with the use of “other-generated” information from social media used by these professionals?

Teams extend understanding of an event by looking to external sources of situationally relevant information such as storm spotters, publicly generated photos and comments posted to online social media (OSM), and communication with community partners. Situationally relevant OSM, specifically Twitter, provides insight to the information behavior of the team. Here we examine the role of proximity and how it impacts decisions on potentially life-saving information sharing in time sensitive information environments: proximity within the team (shared knowledge state) and proximity to the event (hashtag) specifically are addressed.

Digital Object Identifier (DOI)

In summary, a cross comparison of the content analysis and focus group analysis revealed commonalities as well as differences, however, more similarities were identified than differences. The CAF-QIS framework (Bonnici, 2016) provides quality indicators with clear definitions that can be applied consistently across Tweets. Application of the framework during content analysis revealed researcher interpretation of the framework influenced identification of quality indicators. The participants identified indicators found within the CAF-QIS framework (Bonnici, 2016) but referenced the elements of the quality indicators specifically. The focus group participants spoke of content creators, location, photos and videos, and time. Similar to that of the content analysis, participant identification of credibility and trustworthiness indicators are influenced by the interpretation of participants description of credibility indicators. Credibility and trustworthiness contributed to identification of valid Tweets in the focus group whereas quality indicators were identified within the CAF-QIS framework.

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