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Jess Kropczynski, Rob Grace, Julien Coche, Shane Halse, Eric Obeysekare, Aurélie Montarnal, et al. (2018). Identifying Actionable Information on Social Media for Emergency Dispatch. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 428–438). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: Crisis informatics researchers have taken great interest in methods to identify information relevant to crisis events posted by digital bystanders on social media. This work codifies the information needs of emergency dispatchers and first responders as a method to identify actionable information on social media. Through a design workshop with public safety professionals at a Public-Safety Answering Point (PSAP) in the United States, we develop a set of information requirements that must be satisfied to dispatch first responders and meet their immediate situational awareness needs. We then present a manual coding scheme to identify information satisfying these requirements in social media posts and apply this scheme to fictitious tweets professionals propose as actionable information to better assess ways that this information may be communicated. Finally, we propose automated methods from previous literature in the field that can be used to implement these methods in the future.
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Jess Kropczynski, Rob Grace, Shane Halse, Doina Caragea, Cornelia Caragea, & Andrea Tapia. (2019). Refining a Coding Scheme to Identify Actionable Information on Social Media. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: This paper describes the use of a previously established qualitative coding scheme developed through a design workshop with public safety professionals, and applied the schema to social media data collecting during crises. The intention of applying this scheme to existing crisis datasets was to acquire training data for machine learning. Applying the coding scheme to social media data revealed that additional subcategories of the coding scheme are necessary to satisfy information requirements necessary to dispatch first responders to an incident. The coding scheme was refined and adapted into a set of instructions for qualitative coders on Amazon Mechanical Turk. The contribution of this work is a coding scheme that is more directly related to the information needs of public safety professionals. Implications of early results using the refined coding scheme are discussed in terms of proposed automated methods to identify actionable information for dispatch of first responders during emergency incidents.
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Julien Coche, Jess Kropczynski, Aurélie Montarnal, Andrea Tapia, & Frédérick Bénaben. (2021). Actionability in a Situation Awareness world: Implications for social media processing system design. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 994–1001). Blacksburg, VA (USA): Virginia Tech.
Abstract: The field of crisis informatics now has a decade-long history of designing tools that leverage social media to support decision-makers situation awareness. Despite this history, there remains few examples of these tools adopted by practitioners. Recent fieldwork with public safety answering points and first responders has led to an awareness of the need for tools that gather actionable information, rather than situational awareness alone. This paper contributes to an ongoing discussion about these concepts by proposing a model that embeds the concept of actionable information into Endsley's model of situation awareness. We also extend the insights of this model to the design implications of future information processing systems.
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Nathan Elrod, Pranav Mahajan, Monica Katragadda, Shane Halse, & Jess Kropczynski. (2021). An Exploration of Methods Using Social Media to Examine Local Attitudes Towards Mask-Wearing During a Pandemic. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 345–358). Blacksburg, VA (USA): Virginia Tech.
Abstract: During the COVID-19 health crisis, local public offcials expend considerable energy encouraging citizens to comply with prevention measures in order to reduce the spread of infection. During the pandemic, mask-wearing has been accepted among health offcials as a simple preventative measure; however, some local areas have been more likely to comply than others. This paper explores methods to better understand local attitudes towards mask-wearing as a tool for public health offcials' situational awareness when preparing public messaging campaigns. This exploration compares three methods to explore local attitudes: sentiment analysis, n-grams, and hashtags. We also explore hashtag co-occurrence networks as a starting point to begin the filtering process. The results show that while sentiment analysis is quick and easy to employ, the results oer little insight into specific local attitudes towards mask-wearing, while examining hashtags and hashtag co-occurrence networks may be used a tool for a more robust understanding of local areas when attempting to gain situational awareness.
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Nicolas Lalone, Jess Kropczynski, & Andrea Tapia. (2018). The Symbiotic Relationship of Crisis Response Professionals and Enthusiasts as Demonstrated by Reddit's User-Interface Over Time. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 232–244). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Since the Aurora, Colorado movie theater shooting of 2012, the web aggregation community Reddit has been an enthusiast-driven, public-facing source of information about crisis response efforts. We describe the evolution of Reddit's software from the Boston Marathon Bombing of 2013 to the Ferguson unrest throughout 2014. Initially, Reddit was built to aggregate verified news but beginning with the Aurora movie theater shooting, Reddit began to aggregate and verify breaking news. In response to criticism of Reddit's actions during the Boston Marathon Bombing, Reddit re-designed their software in an effort to more accurately mimic crisis response professionals by fostering rigor, information control, and tighter bureaucracy. Reddit's ability to swiftly change its software serves as an example of the possibilities of crisis informatics in practice. We highlight the processes that Reddit has taken to maintain its efficacy even within the current issues surrounding information verification and automated spreading of rumors and falsehoods.
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Rob Grace, Jess Kropczynski, & Andrea Tapia. (2018). Community Coordination: Cooperative Uses of Social Media in Community Emergency Management. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 609–620). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Emergency managers continue to struggle with a lack of staff, information processing tools, and sufficient trust in citizen-reported information to coordinate the use of social media in their communities. To understand possibilities for overcoming these barriers, we conduct interviews with emergency managers using scenarios describing the projective activities of community volunteers disseminating and monitoring social media. We find that coordinating social media use in communities requires alignments with local incident management systems and, in particular, existing sociotechnical infrastructure for managing citizen-reported information. These alignments open limited roles for community volunteers, notably coordinating the redistribution of official information; and stand to reshape the workflows and infrastructures of incident management systems by pushing emergency dispatchers to proactively process indirect reports of incidents obtained on social media, and integrate tools that can access hyperlocal data, curate incident and situational reports, and facilitate sensemaking among officials confronted with multiple information sources.
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Rob Grace, Jess Kropczynski, Scott Pezanowski, Shane Halse, Prasanna Umar, & Andrea Tapia. (2017). Social Triangulation: A new method to identify local citizens using social media and their local information curation behaviors. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 902–915). Albi, France: Iscram.
Abstract: Local citizens can use social media such as Twitter to share and receive critical information before, during, and after emergencies. However, standard methods of identifying local citizens on Twitter discover only a small proportion of local users in a geographic area. To better identify local citizens and their social media sources for local information, we explore the information infrastructure of a local community that is constituted prior to emergencies through the everyday social network curation of local citizens. We hypothesize that investigating social network ties among local organizations and their followers may be key to identifying local citizens and understanding their local information seeking behaviors. We describe Social Triangulation as a method to identify local citizens vis-à-vis the local organizations they follow on Twitter, and evaluate our hypothesis by analyzing users' profile location information. Lastly, we discuss how Social Triangulation might support community preparedness by informing emergency communications planning.
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Rob Grace, Shane Halse, Jess Kropczynski, Andrea Tapia, & Fred Fonseca. (2019). Integrating Social Media in Emergency Dispatch via Distributed Sensemaking. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Emergency dispatchers typically answer 911 calls and relay information to first responders; however, new workflows arise when social media analysts are included in emergency dispatch work. In this study we examine emergency dispatch workflows as distributed sensemaking processes performed among 911 call takers, dispatchers, and social media analysts during simulated emergency dispatch operations. In active shooter and water rescue scenarios, emergency dispatch teams including call takers, dispatchers, and social media analysts make sense of unfolding events by analyzing, aggregating, and synthesizing information provided by 911 callers and social media users during each scenario. Findings from the simulations inform design requirements for social media analysis tools that can help analysts detect, seek, and analyze information posted on social media during a crisis, and protocols for coordinating analysts? sensemaking activities with those of 911 call takers and dispatchers in reconfigured emergency dispatch workflows.
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Shane Errol Halse, Rob Grace, Jess Kropczynski, & Andrea Tapia. (2019). Simulating real-time Twitter data from historical datasets. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: In this paper, we will discuss a system design for simulating social media data based on historical datasets. While many datasets containing data collected from social media during crisis have become publicly available, there is a lack of tools or systems can present this data on the same timeline as it was originally posted. Through the design and use of the tool discussed in this paper, we show how historical datasets can be used for algorithm testing, such as those used in machine learning, to improve the quality of the data. In addition, the use of simulated data also has its benefits in training scenarios, which would allow participants to see real, non-fabricated social media messages in the same temporal manner as found on a social media platform. Lastly, we will discuss the positive reception and future improvements suggested by 911 Public Service Answering Point (PSAP) professionals.
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Shane Halse, Jess Kropczynski, & Andrea Tapia. (2018). Using Metrics of Stability to Identify Points of Failure and Support in Online Information Distribution during a Disaster. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (p. 1121). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: We utilize the 2012 Hurricane Sandy dataset to investigate methods to measure network stability during a crisis. While previous research on information distribution has focused on individuals that are most connected, or most willing to share information, we examined this dataset for indicators of network stability. The value of this measure is to identify the points of failure within the network. The findings in this paper provide support for the use of social network analysis within the realm of crisis response to identify the points of failure within the network.
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