The memnet package provides efficient implementations of network science tools to facilitate research into human (semantic) memory. In its current version, the package contains several methods to infer networks from verbal fluency data, various network growth models, diverse (switcher-) random walk processes, and tools to analyze and visualize networks.

The majority of memnet is written in C++ to deliver maximum performance.

Have questions, found annoying errors, or have need/recommendation for additional functionality? Please don’t hesitate to write me at dirk.wulff@gmail.com or https://github.com/dwulff/memnet. Thanks!