With the recent expansion of social media and the massive outreach these platforms have, the need for social media monitoring has become more important. The specific intent being analysis and sensemaking of actions taken by entities, organizations, and networks that may have the ability to influence narratives or audiences. To achieve this, the Department of Defense (DoD) has made progress in the field concerning analysis of social media intelligence (SOCINT) where intelligence analysts engage in an iterative sensemaking process, encompassing procedures such as locating, gathering, and organizing data. As a result of these actions, the main goal is to develop schemas and hypotheses that support identification of future courses of actions aiding in mitigation strategies.

Current SOCINT tooling and technologies are geared towards the locating and gathering phases of analysis. These tools work to gathering data related to identified topics from social media platforms such as Twitter, Facebook, and Reddit. However, when it comes to the organization of the data, intelligence analysts often resort to tooling not designed for this phase of analysis, such as Microsoft Word or PowerPoint. This paper will focus on potential ways that sensemaking and schema development can be integrated into SOCINT training and tooling. For example, the implementation of an ontology, or folksonomy for structuring and filtering data, as well as the integration of visualizations to identify patterns among the collected data. The objective of investigating training procedure modifications and enhancements is to evaluate mechanisms that are hypothesized to aid analysts in better formulating schemas and interpreting datasets. As a result of this investigation, tooling tailored to schema development can be provided to encourage proper selection for courses of action and analysis directions.

Keywords
MODELING

Additional Keywords
Social Media, Intelligence Analysis, Social Cyber, Schema Development, Sensemaking