27 April 2018 Text motifs: classifying influential individuals and follower networks with language agnostic methods
Author Affiliations +
Abstract
This paper discusses applying automated social media analytics to address challenges facing the OSINT analyst. The growing use and trust of social media presents significant potential for planning, executing, and assessing military information support operations (MISO). The enabling technology for this capability is called SURF, which is a GOTS tool developed to perform what is referred to as ‘group search’ by classifying individuals based on their network features and interactions. This language-agnostic tool has been validated at very high levels of accuracy for classifying users. This same technology can be used to support other critical MISO and commercial sector activities. In this paper, we present the background research, motivation for algorithm development, validation and example usage.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Elizabeth Bowman, Elizabeth Bowman, Tod Hagan, Tod Hagan, Bruce McQueary, Bruce McQueary, Rob Asfar, Rob Asfar, Jose Pascual, Jose Pascual, } "Text motifs: classifying influential individuals and follower networks with language agnostic methods", Proc. SPIE 10653, Next-Generation Analyst VI, 106530J (27 April 2018); doi: 10.1117/12.2307049; https://doi.org/10.1117/12.2307049
PROCEEDINGS
4 PAGES + PRESENTATION

SHARE
Back to Top