Resources: Research Literature

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Several researchers have published peer reviewed articles which document and analyze the ways in which social media is impacting disaster response. The following are noteworthy recent publications that provide new insights about this emerging topic.

  • Alexander, D. (2014). Social Media in Disaster Risk Reduction and Crisis Management. Science and Engineering Ethics, 20(3), 717-733. doi: 10.1007/s11948-013-9502-z
      • In this paper, David E. Alexander examines seven different ways in which social media is used in the emergencies field, including: listening to public debate, monitoring situations, extending emergency response and management, crowd-sourcing and collaborative development, creating social cohesion, furthering causes (including charitable donation) and enhancing research. This paper also discusses how the widespread use of social media may aid in the exposure of corruption and malpractice, though it is crucial to ensure that social media are not abused or misused in emergency situations.
  • Bruns, A., & Liang, Y. E. (2012). Tools and methods for capturing Twitter data during natural disasters. doi: http://dx.doi.org/10.5210/fm.v17i4.3937
      • This article discusses the important role Twitter has played as a medium for many-to-many crisis communication and emergency service outreach. Emergency services are also attempting to source first-hand situational information from Twitter feeds but require flexible and reliable research structure. This article outlines two approaches to the development of such infrastructure: one which builds on a readily available open source platform; and one which establishes a framework by drawing on state-of-the-art technology.
  • Charles-Smith, L. E., Reynolds, T. L., Cameron, M. A., Conway, M., Lau, E. H. Y., Olsen, J. M., . . . Corley, C. D. (2015). Using Social Media for Actionable Disease Surveillance and Outbreak Management: A Systematic Literature Review. PLoS ONE, 10(10), e0139701. doi: 10.1371/journal.pone.0139701
      • This literature review, completed by a social media work group consisting of surveillance practitioners, academic researchers, and other subject matter experts convened by the International Society for Disease Surveillance, was prepared using the PRISMA framework. The literature review focused on two questions: 1) Can social media be integrated into disease surveillance practice and outbreak management to support and improve public health? 2) Can social media be used to effectively target populations, specifically vulnerable populations, to test an intervention and interact with a community to improve health outcomes? Information gleaned from the literature review demonstrates the effectiveness of social media in supporting and improving public health and in identifying target populations for intervention.
  • Cheng, T., & Wicks, T. (2014). Event Detection using Twitter: A Spatio-Temporal Approach. PLoS ONE, 9(6), e97807. doi: 10.1371/journal.pone.0097807
      • This paper details the effectiveness of using space-time scan statistics (STSS) to analyze Twitter feeds and detect an event of interest. The special event used as a case study is the 2013 London helicopter crash. A spatio-temporally significant cluster was found relating to the London helicopter crash. Although the cluster is significant only for a relatively short time, it is rich in information, such as important key words and photographs.
  • Chew, C., & Eysenbach, G. (2010). Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak. PLoS ONE, 5(11), e14118. doi: 10.1371/journal.pone.0014118
      • This article details a study evaluating an “infoveillance” approach, using social media, to measure public perceptions in emergencies. This study uses Twitter during the 2009 H1N1 pandemic as its case study. The study illustrates that 2009 H1N1-related tweets were primarily used to disseminate information from credible sources, but were also a source of opinions and experiences. By using real-time content analysis and knowledge translation research, health authorities can use social media to response to public concerns.
  • Harris Smith S, Bennett KJ, Livinski AA. Evolution of a Search: The Use of Dynamic Twitter Searches During Superstorm Sandy. PLOS Currents Disasters. 2014 Sep 26. Edition 1. doi: 10.1371/currents.dis.de9415573fbf90ee2c585cd0b2314547.
      • This article highlights a two-prong strategy in which the use of a Twitter list paired with subject specific Boolean searches provided increased situational awareness and early event detection during the United States Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedness and Response (ASPR) response to Superstorm Sandy in 2012. To maximize the amount of relevant information that was retrieved, the Twitter list and Boolean searches were dynamic and responsive to real-time developments, evolving health threats, and the informational needs of decision-makers.
  • Huang, Q., & Xiao, Y. (2015). Geographic Situational Awareness: Mining Tweets for Disaster Preparedness, Emergency Response, Impact, and Recovery. ISPRS International Journal of Geo-Information, 4(3), 1549. doi: 10.3390/ijgi4031549
      • 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. A classifier based on logistic regression is also trained and used for automatically mining and classifying the social media messages into various topic categories during various disaster phases. The classification results are useful for emergency managers to identify the transition between phases of disaster management.
  • Neiger, B. L., Thackeray, R., Burton, S. H., Thackeray, C. R., & Reese, J. H. (2013). Use of Twitter Among Local Health Departments: An Analysis of Information Sharing, Engagement, and Action. Journal of Medical Internet Research, 15(8), e177. doi: 10.2196/jmir.2775
      • This paper examines how local health departments (LHDs) use Twitter to share information, engage with followers, and promote action. The study concludes that Twitter is being adopted by LHDs, but is primarily used for one-way communication. There is potential for Twitter to help form partnerships with audiences and involve them as program participants for action leading to improved health.
  • Paul, M. J., & Dredze, M. (2014). Discovering Health Topics in Social Media Using Topic Models. PLoS ONE, 9(8), e103408. doi: 10.1371/journal.pone.0103408
      • This paper describes a topic modeling framework for discovering health topics on Twitter with the goal of understanding what health topics are commonly discussed in social media. A statistical topic model created for this purpose, the Ailment Topic Aspect Model (ATAM) and a system for filtering general Twitter data based on health keywords and supervised classification are detailed. The results of this study showed that it is possible to automatically discover topics that attain statistically significant correlations with ground truth data, despite using minimal human supervision and no historical data to train the model.
  • Poorazizi, M., Hunter, A., & Steiniger, S. (2015). A Volunteered Geographic Information Framework to Enable Bottom-Up Disaster Management Platforms. ISPRS International Journal of Geo-Information, 4(3), 1389. doi: 10.3390/ijgi4031389
      • By using location-aware devices such as smartphones to collect geographic information in the form of geo-tagged text, photos, or videos, and sharing this information through social media, citizens create Volunteered Geographic Information (VGI). This article details the creation of a VGI framework for the discovery of VGI data relevant to disaster management. The addition of quality metrics and a single aggregated source of relevant crisis VGI will allow users to make informed policy choices that could save lives, meet basic humanitarian needs earlier, and perhaps limit environmental and economic damage.
  • Schreck, T., & Keim, D. (2013). Visual Analysis of Social Media Data. Computer, 46(5), 68-75. doi: 10.1109/MC.2012.430
      • This paper and video details a prototype system for visual-interactive analysis of large geo-referenced microblog datasets and its application to the VAST 2011 Challenge dataset. The dataset models an epidemic outbreak in a fictitious metropolitan area. The visual-interactive analysis system can detect the epidemic and analyze its development over time.
  • Simon, T., Goldberg, A., Aharonson-Daniel, L., Leykin, D., & Adini, B. (2014). Twitter in the Cross Fire—The Use of Social Media in the Westgate Mall Terror Attack in Kenya. PLoS ONE, 9(8), e104136. doi: 10.1371/journal.pone.0104136
      • During the September 2013 attack on the Westgate mall in Kenya, Twitter became a crucial channel of communication between the government, emergency responders and the public, facilitating the emergency management of the event. This paper presents the main activities, use patterns and lessons learned from the use of social media during the crisis. Using TwitterMate, a system developed to collect, store and analyze tweets, the main hashtags generated by the crowd and specific Twitter accounts of individuals, emergency responders and NGOS, were followed throughout the four day siege. The creation of a standard operating procedure is suggested to enable multiple responders to monitor, synchronize and integrate their social media feeds during emergencies.
  • Song, L., & Hatzinakos, D. (2008). Real-Time Communications in Large-Scale Wireless Networks. International Journal of Digital Multimedia Broadcasting, 2008, 16. doi: 10.1155/2008/586067
      • This paper details an emerging need to realizing real-time quality of service (QoS) over multihop wireless communications in large-scale wireless networks. The applications can include wireless mesh infrastructure for broadband Internet access supporting multimedia services, visual sensor networks for surveillance, and disaster-relief networks. This paper proposes the use of large-scale cognitive networking methods to resolve the wireless multihop challenges. The successful results of this method are supported by analysis, simulations, and experiments.
  • Towers, S., Afzal, S., Bernal, G., Bliss, N., Brown, S., Espinoza, B., . . . Castillo-Chavez, C. (2015). Mass Media and the Contagion of Fear: The Case of Ebola in America. PLoS ONE, 10(6), e0129179. doi: 10.1371/journal.pone.0129179
      • In the weeks following the first imported case of Ebola in the U.S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health. Public interest in these events was high, as reflected in the millions of Ebola-related internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time predication of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. This paper examined daily Ebola-related Internet search and Twitter data and applied the parameters of a mathematical contagion model to the data to determine if the new coverage was a significant factor in the temporal patterns in Ebola-related data.
  • Zhang, N., Huang, H., Su, B., Zhao, J., & Zhang, B. (2014). Information Dissemination Analysis of Different Media towards the Application for Disaster Pre-Warning. PLoS ONE, 9(5), e98649. doi: 10.1371/journal.pone.0098649
      • This paper establishes models of information dissemination for six typical information media, including short message service (SMS), microblogs, news portals, cell phones, television, and oral communication. Then, the information dissemination capability of each medium concerning individuals of different ages, genders, and residential areas was simulated, and the dissemination characteristics were studied. The models and results produced are essential for improving the efficiency of information dissemination for the purpose of disaster pre-warning and for formulating emergency plans which help reduce the possibility of injuries, deaths, and other losses in a disaster.