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Twitter is increasingly of interest as a social media that can be used to help mitigate disasters. In this paper, we describe the strength and limitations of Twitter in this context, and identify the features needed in a twitter system to support disaster planning, warning and response. To orient the discussion, we describe a local context, Padang Indonesia. We then illustrate the kind of system needed by describing our implementation of TWRsms – a twitter tracking and analysis system for Padang Indonesia. Our implementation collects and analyzes tweets from the shoreline city of Padang Indonesia. This area is exposed to considerable risk from tsunamis, and the purpose of our system is to provide Indonesians information to plan for response to tsunamis, to provide immediate feedback about relevant tweeters in the wake of tsunami warnings, to support an early warning system, and to allow long-term research into how Indonesians tweet about disasters and other topics. We conclude by reviewing ongoing challenges: considering technical, social and policy issues and the challenge for science and the practical challenges of deploying such a system. [ABSTRACT FROM AUTHOR]

OBJECTIVE: The aim of this study was to compare information sharing and advice networks' relationships with patient safety outcomes. BACKGROUND: Communication contributes to medical errors, but rarely is it clear what elements of communication are key. METHODS: We investigated relationships of information-sharing and advice networks to patient safety outcomes in 24 patient care units from 3 hospitals over 7 months. Web-based questionnaires completed via Android tablets provided data to create 2 networks using ORA, a social network analysis application. Each hospital provided nurse-sensitive patient safety outcomes. RESULTS: In both networks, medication errors correlated positively with node count and average distance and negatively with clustering coefficient. Density and weighted density negatively correlated with medication errors and falls in both networks. Eigenvector and total degree centrality correlated negatively with both safety outcomes, whereas betweenness centrality positively related to falls in the information-sharing network. CONCLUSION: Technology-enabled social network analysis data collection is feasible and can provide managers actionable system-level information. [ABSTRACT FROM AUTHOR]

Social media is playing a growing role in disaster management and response. Expectations are that such media can be critical for sending alerts, identifying critical needs, and focusing response. However, for social media to be used in that way, it will be necessary to understand how social media is used during normal, i.e., non-disaster periods. Herein we examine the use of a particular social media, Twitter, and assess its value for disaster management with a focus on planning and early warnings. Our focus is Padang Indonesia, and the potential use of Twitter to support tsunami warning and response. We assess alternative collection strategies and analyze Twitter usage under normal conditions and then use this information to identify the strengths and weaknesses of this data in supporting disaster planning and early warning in terms of coverage, spatio-temporal patterns, and identification of opinion leaders. We find that while one can potentially leverage Twitter for disaster management, careful collection, assessment, and coordination with official disaster Twitter sites and local on-scene Twitter opinion leaders will be critical from a preparedness and early warning perspective. Guidelines for harnessing Twitter data for such uses are provided. [ABSTRACT FROM AUTHOR]