HASHKAT is a dynamic network simulation tool designed to model the growth of and information propagation through an online social network. It is an agent-based, Kinetic Monte Carlo engine capable of simulating online networks such as Facebook, Twitter, LinkedIn, etc.
HASHKAT incorporates all elements of online social networks including multiple user profiles (e.g. standard users, organizations, celebrities, and bots), user messaging, trending topics, and advertising. Agents within the network make decisions (e.g. follow, unfollow, broadcast, and rebroadcast) based on a variety of user defined constraints on signal propagation to model language, region, ideology, musical interests, and humour.
HASHKAT allows for simulation of a realistic online social network, enabling users to test hypotheses for growth mechanisms and scenarios for information propagation. As it solves the forward problem, HASHKAT can be used with Big Data analytics tools to test data collection protocols and ensure inverse model validity.
HASHKAT is a fully cross-platform tool: it works natively on Windows 10, OS X, and Linux platforms.