Although the tools for OSINT collection are constantly evolving, the methods used by the tools themselves change less dramatically. Most tools use lexical analysis, network analysis, geospatial analysis, or a combination of these methods to isolate, describe, and analyze data. All three methods existed long before their application to Internet-based content, but the vast proliferation of social media platforms and the ever-increasing ease with which individuals can access the Internet make that environment rich for intelligence collection. Furthermore, just as the transition from Web 1.0 to Web 2.0 has exponentially increased the amount of user-generated data available to parse and analyze for specific characteristics, the transition to Web 3.0— where machine learning and natural language processing will be dominant—is already changing the efficiency of these methods for sorting, translating, and analyzing data for intelligence purposes.
Distinguishing between the proliferating commercially available open-source analytic tools can be difficult, because of their abundance and poor descriptions. Identifying the specific components of the methods they use, however, provides a rubric by which to evaluate and compare capabilities. Tools can be compared in terms of the number of analytic methods they can employ and their speed, accuracy, and capacity for performing analyses.