How to cluster a link traversal dataset
@Shagun's answer is right actually. I just expand it!

There are 2 different approaches to your problem:

Graph Approach


As stated in @Shagun's answer you have a weighted directed graph and you want to cluster the paths. I mention again because it's important to know that your problem is not a Graph Clustering or Community Detection problem where vertices are clustered!
Cunstructing a Graph in networkx using the last two column of the data, you can add time spent as weight and users who passed that link as an edge attribute. After all you'll have different features for clustering: the set of all vertices an individual ever met in the graph, total, mean and std of time spent, shortest path distribution parameters, ... which can be used for clustering the user behaviors.


Standard Data


All above can be done by reading data efficiently in a matrix. If you consider each edge for a specified user as a single row (i.e. you'll have MxN rows where M is the number of users and N the number of edges in case you stick with 100 case!) and add properties as columns you'll probably able to cluster behaviors. if a user passed an edge n times, in the row corresponding to that user and that edge add a count column with value n and same for time spend, etc. Starting and ending edges are also informative. Be careful that node names are categorical variables.


Regarding clustering algorithms you can find enough if you have a quick look at SKlearn.

Hope it helped.
Good Luck :)