Today’s analysts must process increasing amounts of information, including “Twitter-INT” 1 (social information such as Facebook, You-Tube videos, blogs, Twitter), as well as discern threat signatures in “gray zone” or hybrid conflicts distinguished by both aggression and ambiguity. The information environment is characterized by continuous change: the growing volume of data and the speed at which data is created and new influence tactics developed. Rebecca Goolsby wrote, “…the creation of hoaxes, hate speech, and other attempts at crowd manipulation and exploitation reveal the darker side of the social media phenomenon; the targeted “social-cyberattack” is rapidly coming of age.” The goal is to be able to describe, diagnose, and predict actions/behaviors/events based on an environment in which both humans and bots are attempting to influence, in which disinformation is common and curation and fact checking are rare The information environment is changing much faster than the ability of analysts to process and make meaning about actors, events and influence. Learning how to “surf” the information environment, rather than drown in the proverbial big data will require a new approach. Leveraging the fundamentals and “tricks of the trade” used by data scientists/analysts can serve to close the gap. This paper will highlight exemplar methods and tools and provide contextualized examples of how they improve the ability to describe and diagnose, and, ultimately, make meaning.