This Projects contains the code for a fast implementation of both the RandomSurfer- and the PageRank-Algorithm. The project was part of a mandatory assignment in the course course Linear Algebra and Optimization, but is highly connected to the Network Science Classes within the 1st years Programming-Course. The Output Data has been collected for 10.000.000 iterations of the RandomSurfer and 100 iterations of the PageRank-Algorithm.

1. Install all necessary modules needed (networkx, random, matplotlib, os, csv, timeit) by using pip install <module>

2. Make sure to have the the sample datasets in a directory called "PageRankExampleData". Also, don't rename the files, as the program will then not recognize them.

3. Change the parameters of the main function and helper functions to get differnt outputs. The Docstrings will guide you through the meaning of each variable.

Have fun!

Only the .py file is being maintained and is working. The code has not yet been transferred into a working .ipynb (Jupyter Notebook).