Emergency Managers\u27 Perspectives on Social Media Use for Situational Awareness During Disasters

Emergency managers are responsible for protecting lives, property, and the environment. Decisions are made based on the availability of information provided to emergency managers from the disaster site. Communication between first responders and emergency managers is crucial for obtaining situational awareness for decision-making purposes during disasters. The purpose of this qualitative explanatory case study was to understand the perspectives of emergency managers regarding the use of social media in obtaining situational awareness and providing disaster-specific information necessary for emergency managers to make informed decisions during disasters. The theoretical framework for this study was based on Endsley’s situational awareness model and Rowley’s data, information, knowledge, wisdom hierarchy. Data were collected from semistructured interviews with 11 participants. The results of the 6-step thematic analysis revealed the disaster-specific information emergency managers need to make informed decisions, current situational awareness strategies, the perspectives of emergency managers regarding social media, and training gaps associated with social media and its use for situational awareness. Findings may be used to promote positive social change to improve the use of social media in disaster response operations that aid emergency managers in meeting response priorities, including protection of life, property, and the environment

Expanding Awareness: Comparing Location, Keyword, and Network Filtering Methods to Collect Hyperlocal Social Media Data

Opportunities to collect real-time social media data during a crisis remain limited to location and keyword filtering despite the sparsity of geographic metadata and the tendency of keyword-based methods to capture information posted by remote rather than local users. Here we introduce a third, network filtering method that uses social network ties to infer the location of social media users in a geographic community and collect data from networks of these users during a crisis. In this paper we compare all three methods by analyzing the distribution of situational reports of infrastructure damage and service disruption across location, keyword, and network-filtered social media data during a weather emergency. We find that network filtering doubles the number of situational reports collected in real-time compared to location and keyword filtering alone, but that all three methods collect unique reports that can support situational awareness of incidents occurring across a community

Passive Visual Analytics of Social Media Data for Detection of Unusual Events

Now that social media sites have gained substantial traction, huge amounts of un-analyzed valuable data are being generated. Posts containing images and text have spatiotemporal data attached as well, having immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. However, the large volume of unstructured social media data hinders exploration and examination. To analyze such social media data, the S.M.A.R.T system provides the analyst with an interactive visual spatiotemporal analysis and spatial decision support environment that assists in evacuation planning and disaster management. S.M.A.R.T fetches data from various social media sources and arranges them in a perceivable manner, which is visually appealing. This in turn is a huge aid in finding and understanding abnormal events. Introducing a passive mode makes the tool more efficient, where it automatically detects idle time and gives a summary of all the anomalies encountered in the inactive period as soon as the analyst resumes monitoring. Using the tool, the analyst can first extract major topics from a set of selected messages and rank them probabilistically. The case studies in the past show improved situational awareness by using the methods mentioned before

GeoSocial: exploring the usefulness of social media mining in the applied natural geohazard sciences

Obtaining real-time information about a geohazard event as it unfolds, such as a flood or earthquake, used to be largely limited to the professional media. Nowadays, obtaining news stories from social media (e.g. Facebook, Twitter, YouTube, Flickr etc.), directly as they unfold, is becoming the ‘norm’ for many in society. The Haitian Earthquake in January 2010 and the Great East Japan Earthquake in March 2011, provided some of the first natural hazard examples, to really demonstrate the power of social media over traditional news sources for obtaining, live information from which people and authorities could gain situational awareness

Uses of Social Media to Inform Operational Response and Recovery During an Airport Emergency

TRB\u27s Airport Cooperative Research Program (ACRP) Synthesis 82: Uses of Social Media to Inform Operational Response and Recovery During an Airport Emergency summarizes airport practices and tools used by airport emergency managers. Using social media for emergency management, airports glean information and intelligence from the stream of posts and messages passing through social media and then apply this information to enhance situational awareness and resource allocation decisions by emergency managers. Such uses raise the stakes for timeliness of data extraction and validation of the results, especially if the information is going to be used for resource allocation and other decision making

empathi: An ontology for Emergency Managing and Planning about Hazard Crisis

In the domain of emergency management during hazard crises, having sufficient situational awareness information is critical. It requires capturing and integrating information from sources such as satellite images, local sensors and social media content generated by local people. A bold obstacle to capturing, representing and integrating such heterogeneous and diverse information is lack of a proper ontology which properly conceptualizes this domain, aggregates and unifies datasets. Thus, in this paper, we introduce empathi ontology which conceptualizes the core concepts concerning with the domain of emergency managing and planning of hazard crises. Although empathi has a coarse-grained view, it considers the necessary concepts and relations being essential in this domain. This ontology is available at https://w3id.org/empathi/

Community Segmentation and Inclusive Social Media Listening

Social media analytics provide a generalized picture of situational awareness from the conversations happening among communities present in social media channels that are that are, or risk being affected by crises. The generalized nature of results from these analytics leaves underrepresented communities in the background. When considering social media analytics, concerns, sentiment, and needs are perceived as homogenous. However, offline, the community is diverse, often segmented by age group, occupation, or language, to name a few. Through our analysis of interviews from professionals using social media as a source of information in public service organizations, we argue that practitioners might not be perceiving this segmentation from the social media conversation. In addition, practitioners who are aware of this limitation, agree that there is room for improvement and resort to alternative mechanisms to understand, reach, and provide services to these communities in need. Thus, we analyze current perceptions and activities around segmentation and provide suggestions that could inform the design of social media analytics tools that support inclusive public services for all, including persons with disabilities and from other disadvantaged groups.publishedVersionPaid open acces