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Title Crisis Communication: A Comparative Study of Communication Patterns across Crisis Events in Social Media
Authors Hernán Sarmiento, Bárbara Poblete
Publication date 2021
Abstract Valuable and timely information about crisis situations
such as
natural disasters, can be rapidly obtained from user-generated content in
social media. This has created an emergent research field that has focused
mostly on the problem of filtering and classifying potentially relevant
messages during emergency situations. However, we believe important insight
can be gained from studying online communications during disasters at a more
comprehensive level. In this sense, a higher-level analysis could allow us
to understand if there are collective patterns associated to certain
characteristics of events. Following this motivation, we present a novel
comparative analysis of 41 real-world crisis events. This analysis is based
on textual and linguistic features of social media messages shared during
these crises. For our comparison we considered hazard categories (i.e.,
human-induced and natural crises) as well as subcategories (i.e.,
intentional, accidental and so forth). Among other things, our results show
that using only a small set of textual features, we can differentiate among
types of events with 75% accuracy. Indicating that there are clear patterns
in how people react to different extreme situations, depending on, for
example, whether the event was triggered by natural causes or by human
action. These findings have implications from a crisis response perspective,
as they will allow experts to foresee patterns in emerging situations, even
if there is no prior experience with an event of such
characteristics.
Pages 1711-1720
Conference name ACM Symposium on Applied Computing
Publisher ACM Press (New York, NY, USA)
Reference URL View reference page