In this paper, we examine the socio-technical impact that social media has had on coordination between professional emergency responders and digital volunteers. Drawing from the research literature, we outline the problem space and explore ways to improve coordination and collaboration between these two groups. Possible improvements include mediators, revisiting trust, emergency policy and process changes, a bounded social environment, digital volunteer data as context, and computational solutions. As the space matures and collaboration improves, we predict that professional responders will begin to rely on the data and products produced by digital volunteers. Volunteer groups will be challenged to mature as well, to develop volunteer management systems, permanent staff, data management practices, and training for new volunteers to ensure consistent response to professional responders as needed.
Sentiment analysis has been widely researched in the domain of online review sites with the aim of generating summarized opinions of users about different aspects of products. However, there has been little work focusing on identifying the polarity of sentiments expressed by users during disaster events. Identifying such sentiments from online social networking sites can help emergency responders understand the dynamics of the network, e.g., the main users' concerns, panics, and the emotional impacts of interactions among members. In this paper, we perform a sentiment analysis of tweets posted on Twitter during the disastrous Hurricane Sandy and visualize online users' sentiments on a geographical map centered around the hurricane. We show how users' sentiments change according not only to their locations, but also based on the distance from the disaster. In addition, we study how the divergence of sentiments in a tweet posted during the hurricane affects the tweet retweetability. We find that extracting sentiments during a disaster may help emergency responders develop stronger situational awareness of the disaster zone itself.
A new, citizen science‐based, aurora observing and reporting platform has been developed with the primary aim of collecting auroral observations made by the general public to further improve the modeling of the aurora. In addition, the real‐time ability of this platform facilitates the combination of citizen science observations with auroral oval models to improve auroral visibility nowcasting. Aurorasaurus provides easily understandable aurora information, basic gamification, and real‐time location‐based notification of verified aurora activity to engage citizen scientists. The Aurorasaurus project is one of only a handful of space weather citizen science projects and can provide useful results for the space weather and citizen science communities. Early results are promising with over 2000 registered users submitting over 1000 aurora observations and verifying over 1700 aurora sightings posted on Twitter.
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