Three reading suggestions on Social media and Crisis/Emergencies/Mass Disruptions #ISCRAM

The ISCRAM 2012 conference is now on its second day in Vancouver Canada. The conference has been great both in terms of good research and in terms of networking opportunities with fellow researchers. So far, I would like to present three papers that could be of interest to look a bit deeper into. These papers cover aspects of social media and how the public and government agencies use social media. The papers also cover various aspects on how to make use of insights in social media to support and improve response work. In a few days, all papers from the conference will be published on the website. Meanwhile, download, read and discuss the following papers with your friends at work.

[PDFLearning from the Crowd: Collaborative Filtering Techniques for Identifying On-the-Ground Twitterers during Mass Disruptions 
Kate Starbird, Grace Muzny, Leysia Palen

Social media tools, including the microblogging platform Twitter, have been appropriated during mass disruption events by those affected as well as the digitally-convergent crowd. Though tweets sent by those local to an event could be a resource both for responders and those affected, most Twitter activity during mass disruption events is generated by the remote crowd. Tweets from the remote crowd can be seen as noise that must be filtered, but another perspective considers crowd activity as a filtering and recommendation mechanism. This paper tests the hypothesis that crowd behavior can serve as a collaborative filter for identifying people tweeting from the ground during a mass disruption event. We test two models for classifying on-the-ground Twitterers, finding that machine learning techniques using a Support Vector Machine with asymmetric soft margins can be effective in identifying those likely to be on the ground during a mass disruption event.

[PDFConnected Communications: Network Structures of Official Communications in a Technological Disaster 
Jeannette N. Sutton, Britta Johnson, Mathew Greczek, Emma S. Spiro, Sean M. Fitzhugh, and Carter T. Butts

Informal online communication channels are being utilized for official communications in disaster contexts. Channels such as networked microblogging enable public officials to broadcast messages as well as engage in direct communication exchange with individuals. Here we investigate online information exchange behaviors of a set of state and federal organizations during the Deepwater Horizon 2010 oil spill disaster. Using data from the popular microblogging service Twitter, we analyze the roles individual organizations play in the dissemination of information to the general public online, and the conversational microstructure of official posts. We discuss characteristics and features of following networks, centrality, and conversational dynamics that may affect information exchange in disaster. This research provides insight into the use of networked communications during an event of heightened public concern, describes implications of conversational features, and suggests directions for future research.

[PDFTowards a realtime Twitter analysis during crises for operational crisis management 
Teun Terpstra, R. Stronkman, A. de Vries, G.L. Paradies

Today’ s  crises  attract  great  attention  on  social  media,  from  local  and  distant  citizens  as  well  as  from   news media. This study investigates the possibilities of real-time and automated analysis of Twitter messages during crises. The analysis was performed through application of an information extraction tool to nearly 97,000 tweets that were published shortly before, during and after a storm hit the Pukkelpop 2011 festival in Belgium. As soon as the storm hit the festival tweet activity increased exponentially, peaking at 576 tweets per minute. The extraction tool enabled analyzing tweets through predefined (geo)graphical displays, message content filters (damage, casualties) and tweet type filters (e.g., retweets). Important topics that emerged  were  ‘early  warning  tweets’,  ‘rumors’  and  the  ‘self- organization  of  disaster  relief’  on  Twitter .  Results  indicate  that  automated  filtering  of  information   provides valuable information for operational response and crisis communication. Steps for further research are discussed.

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