Social Media Analytics: A New Approach for Cyberspace Enabled Understanding of Operational Environments

摘要

The purpose of this paper is to highlight the need to increase discourse within the Army on the impacts of cyberspace on operational environments. Current Army doctrine emphasizes network defense and offensive strike capabilities for cyberspace activities, but does not expound on focusing advanced analytical tools for increasing shared understanding of the cyberspace information environment; then using that understanding to solve problems existing in a dual cyberspace-land domain. Global interconnectedness and the speed of change demand a new approach. This research borrows from data analytics, social media, systems theory, sociology, and contemporary U.S. Army and Joint Doctrine. The paper uses the Army Design Methodology (ADM) to provide a common lexicon and model. The question for operational artists given the explosion of information technology over the last ten years is, 'How does the Army at corps level Joint Task Forces and below leverage cognitive information from cyberspace to create a more complete understanding of operational environments.' This monograph explores Social Media Analytics (SMA) as a capability for providing Army commanders and staffs with cyberspace tools for generating human centric understanding. The research addresses SMA applied to a gap in contemporary Joint and Army doctrine, and evaluates SMA as an approach to bridging that gap. The gap analysis and approach provide evidence to the viability of SMA as a tool for increasing shared understanding within operational echelons for dual domain environmental framing. The capability fulfills a requirement using open sources of data enabling a high degree of distribution. The topic is pertinent for military practitioners because SMA, and user generated content in cyberspace, present opportunities to increase operational tempo and the adaptability of Army operational and tactical level echelons by providing near-real time understanding through trending.