Social Network Collaboration for Crisis Response Operations: Developing a Situational Awareness (SA) Tool to Improve Haiti's Interagency Relief Efforts.

摘要

The earthquake in Haiti represents an event of catastrophic scale. Relief efforts were thwarted by blocked roads and ruined runways. Relief organizations assisted in the effort using adhoc approaches but could have benefited from improved Situational Awareness (SA). This thesis develops a new model and methodology, based on data collected following the Haiti earthquake that combines both text-mining methods with 3D graphics. This interpretive approach provides a qualitative improvement on the currently available graphic depictions of such data. Text mining is performed using Lexical Link Analysis (LLA), which tracks and links word pairs, and then visually depicts correlations between discovered words, themes, and entities, thus revealing how they are related to each other in terms of both relationship and content. Our findings reveal discovered patterns of self-organization within this crisis situation, and can demonstrate a dynamic, situational awareness tool that can be executed by a thin client to analyze and determine social-organization collaboration and self-organization for leaders to leverage. This effort can eventually help to create a real-time feedback loop to inform decision maker's organizational awareness, improve organization-to-organization collaboration, and perhaps better allocate resources to areas requiring relief operations.