Using Social Media to Enhance Emergency Situation Awareness: Extended Abstract

By Jie Yin, Andrew Lampert, Mark A. Cameron, Bella Robinson, Robert Power. International Joint Conference on Artificial Intelligence, 2015

601 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4ec2f5eda8872d5d18e53eaeba36b8704e58e128

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Citations in the corpus

Real-Time Crisis Mapping of Natural Disasters Using Social Media (2014, background): “Overall the aim is to build up a coherent situation assessment picture [3] [4] [5] and present it to emergency responders, civil protection authorities and the general public to help coordinate response efforts and improve overall awareness.”
CrisisLex: A Lexicon for Collecting and Filtering Microblogged Communications in Crises (2014, background): “Yin et al. (2012) designed a system for leveraging microblog data during disasters; their data capture module is close in scope with our work, yet it makes no distinction between disasters and other events.”
EvoRiver: Visual Analysis of Topic Coopetition on Social Media (2014, background): “, the number of occurrence of a word in a tweet) to generate feature vectors considering tweets are always short [45].”
Depression detection from social network data using machine learning techniques (2018, background): “…consists of five emotional variables (positive, negative, sad, anger, anxiety), three temporal categories (present focus, past focus and future focus), and 9 standard linguistic dimensions (e.g., articles, prepositions, auxiliary verb, adverbs, conjunctions, pronoun, verbs and nega-tions) [30–36].”
Processing Social Media Messages in Mass Emergency (2014, methodology): “For instance, ESA [Yin et al. 2012; Cameron et al. 2012] aims at enhancing situational awareness with respect to crises induced by natural hazards, particularly earthquakes.”
Detection and Resolution of Rumours in Social Media (2017, background): “…media has been found useful for information gathering and coordination in different situations, including emergencies [Yates and Paquette 2011; Yin et al. 2012; Procter et al. 2013a], protests [Trottier and Fuchs 2014; Agarwal et al. 2014] and natural hazards [Vieweg et al. 2010; Middleton et…”
A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management (2015, background): “Another group of studies seek to identify useful information from social media that could be valuable for improving situation awareness (Yin et al. 2012), i.e. for improving ‘ the perception of elements in the environment within a volume of time and space, the comprehension of their meaning, and…”