Journal ArticleDOI
Understanding social media data for disaster management
Yu Xiao,Qunying Huang,Kai Wu +2 more
TLDR
A novel model to explain the number of tweets by mass, material, access, and motivation (MMAM) is developed and it is found that community socioeconomic factors are more important than population size and damage levels in predicting disaster-related tweets.Abstract:
Social media data are increasingly being used in disaster management for information dissemination, establishment of situational awareness of the “big picture” of the disaster impact and emerged incidences over time, and public peer-to-peer backchannel communications Before we can fully trust the situational awareness established from social media data, we need to ask whether there are biases in data generation: Can we simply associate more tweets with more severe disaster impacts and therefore higher needs for relief and assistance in that area? If we rely on social media for real-time information dissemination, who can we reach and who has been left out? Due to the uneven access to social media and heterogeneous motivations in social media usage, situational awareness based on social media data may not reveal the true picture In this study, we examine the spatial heterogeneity in the generation of tweets after a major disaster We developed a novel model to explain the number of tweets by mass, material, access, and motivation (MMAM) Empirical analysis of tweets about Hurricane Sandy in New York City largely confirmed the MMAM model We also found that community socioeconomic factors are more important than population size and damage levels in predicting disaster-related tweetsread more
Citations
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Journal ArticleDOI
Geographic Situational Awareness: Mining Tweets for Disaster Preparedness, Emergency Response, Impact, and Recovery
Qunying Huang,Yu Xiao +1 more
TL;DR: This paper makes an initial effort in coding social media messages into different themes within different disaster phases during a time-critical crisis by manually examining more than 10,000 tweets generated during a natural disaster and referencing the findings from the relevant literature and official government procedures involving different disaster stages.
Journal ArticleDOI
Social media analytics for natural disaster management
Zheye Wang,Xinyue Ye +1 more
TL;DR: A schema is proposed to categorize the gathered articles into 15 classes and facilitate the generation of data analysis tasks and suggest research opportunities and challenges in fusing social media data with authoritative datasets, i.e. census data and remote-sensing data.
Journal ArticleDOI
Rapid flood inundation mapping using social media, remote sensing and topographic data
TL;DR: In this paper, the authors present a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping.
Journal ArticleDOI
Event classification and location prediction from tweets during disasters
TL;DR: The Twitter post in a flood related disaster is investigated and an algorithm to identify victims asking for help is proposed, which is first of its kind, aimed at helping victims during disasters based on their tweets.
Journal ArticleDOI
Social media for intelligent public information and warning in disasters: An interdisciplinary review
TL;DR: The author envisions the intelligent public information and warning in disaster based on social media, which has three functions: efficiently and effectively acquiring disaster situational awareness information, supporting self-organized peer-to-peer help activities, and enabling the disaster management agencies to hear from the public.
References
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Proceedings ArticleDOI
Microblogging during two natural hazards events: what twitter may contribute to situational awareness
TL;DR: Analysis of microblog posts generated during two recent, concurrent emergency events in North America via Twitter, a popular microblogging service, aims to inform next steps for extracting useful, relevant information during emergencies using information extraction (IE) techniques.
Journal ArticleDOI
Digital divide research, achievements and shortcomings
TL;DR: In this article, the authors made an inventory of 5 years of digital divide research (2000-2005) and focused on three questions: (1) To what type of inequality does the digital divide refer? (2) What is new about the inequality of access to and use of ICTs as compared to other scarce material and immaterial resources? (3) Do new types of inequality exist or rise in the information society?
Proceedings ArticleDOI
Twitter under crisis: can we trust what we RT?
TL;DR: The behavior of Twitter users under an emergency situation is explored and it is shown that it is posible to detect rumors by using aggregate analysis on tweets, and that the propagation of tweets that correspond to rumors differs from tweets that spread news.
Proceedings ArticleDOI
Why we tag: motivations for annotation in mobile and online media
Morgan G. Ames,Mor Naaman +1 more
TL;DR: The incentives for annotation in Flickr, a popular web-based photo-sharing system, and ZoneTag, a cameraphone photo capture and annotation tool that uploads images to Flickr are investigated to offer a taxonomy of motivations for annotation along two dimensions (sociality and function).
Journal ArticleDOI
Crowdsourcing geographic information for disaster response: a research frontier
TL;DR: Geographic information created by amateur citizens, often known as volunteered geographic information, has recently provided an interesting alternative to traditional authoritative information from mapping agencies and corporations, and several recent papers have provided the beginnings of a literature on the more fundamental issues raised by this new source.