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Effects of Disaster Characteristics on Twitter Event Signature
Author(s) -
Haji Mohammad Saleem,
Yishi Xu,
Derek Ruths
Publication year - 2014
Publication title -
procedia engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.32
H-Index - 74
ISSN - 1877-7058
DOI - 10.1016/j.proeng.2014.07.053
Subject(s) - foreknowledge , event (particle physics) , content (measure theory) , social media , signature (topology) , scale (ratio) , computer science , data science , geography , world wide web , mathematics , cartography , mathematical analysis , philosophy , physics , geometry , epistemology , quantum mechanics
Twitter has emerged as a platform that is heavily used during disasters. Therefore, as an event unfolds, it generates varying levels of online engagement from victims as well as onlookers (both physical and virtual). Because methods for mining disaster-related content at scale must contend with the problem of filtering out vast numbers of unrelated posts, any prior knowledge about the characteristics of disaster-related content in the live Twitter feed may help improve the recovery of relevant posts. In this study, we consider the relative abundance of a disasters Twitter content over time (both relative to total event-related content and relative to the overall volume of content generated on Twitter). We refer to this time-varying abundance as the events signature. In an analysis of three different disasters, we find that event signatures are qualitatively different. These differences can be explained in terms of several characteristics of disasters: foreknowledge, duration, severity, and news media engagement

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