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Valerio Lorini, Carlos Castillo, Steve Peterson, Paola Rufolo, Hemant Purohit, Diego Pajarito, et al. (2021). Social Media for Emergency Management: Opportunities and Challenges at the Intersection of Research and Practice. 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. 772–777). Blacksburg, VA (USA): Virginia Tech.
Abstract: This paper summarizes key opportunities and challenges identified during the workshop “Social Media for Disaster Risk Management: Researchers Meet Practitioners” which took place online in November 2020. It constitutes a work-in-progress towards identifying new directions for research and development of systems that can better serve the information needs of emergency managers. Practitioners widely recognize the potential of accessing timely information from social media. Nevertheless, the discussion outlined some critical challenges for improving its adoption during crises. In particular, validating such information and integrating it with authoritative information and into more traditional information systems for emergency managers requires further work, and the negative impacts of misinformation and disinformation need to be prevented.
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Valerio Lorini, Javier Rando, Diego Saez-Trumper, & Carlos Castillo. (2020). Uneven Coverage of Natural Disasters in Wikipedia: The Case of Floods. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 688–703). Blacksburg, VA (USA): Virginia Tech.
Abstract: The usage of non-authoritative data for disaster management provides timely information that might not be available through other means. Wikipedia, a collaboratively-produced encyclopedia, includes in-depth information about many natural disasters, and its editors are particularly good at adding information in real-time as a crisis unfolds. In this study, we focus on the most comprehensive version of Wikipedia, the English one. Wikipedia offers good coverage of disasters, particularly those having a large number of fatalities. However, by performing automatic content analysis at a global scale, we also show how the coverage of floods in Wikipedia is skewed towards rich, English-speaking countries, in particular the US and Canada. We also note how coverage of floods in countries with the lowest income is substantially lower than the coverage of floods in middle-income countries. These results have implications for analysts and systems using Wikipedia as an information source about disasters.
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Valerio Lorini, Carlos Castillo, Francesco Dottori, Milan Kalas, Domenico Nappo, & Peter Salamon. (2019). Integrating Social Media into a Pan-European Flood Awareness System: A Multilingual Approach. 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 a prototype system that integrates social media analysis into the European Flood Awareness
System (EFAS). This integration allows the collection of social media data to be automatically triggered by flood
risk warnings determined by a hydro-meteorological model. Then, we adopt a multi-lingual approach to find
flood-related messages by employing two state-of-the-art methodologies: language-agnostic word embeddings
and language-aligned word embeddings. Both approaches can be used to bootstrap a classifier of social media
messages for a new language with little or no labeled data. Finally, we describe a method for selecting relevant and
representative messages and displaying them back in the interface of EFAS.
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