Date of Award


Document Type

Thesis (Undergraduate)

Department or Program

Department of Computer Science

First Advisor

Dan Rockmore


In this paper, we develop an interactive system to navigate information networks as a space with geometry, assigning each node in the network to geographical coordinates, and with that the ability to navigate as if on a map. A map-based rendering of the network gives the user the ability to understand meta-relationships (i.e., non-link-based relationships) that exist in the dataset that are lost with a traditional web search and (hyper-)link navigation. This requires first being able to represent the information corpus in such a way as to enable a quantifiable notion of similarity between the information nodes. A t-SNE (t-distributed stochastic neighbor embedding) model then finds an optimal embedding of the nodes in two-dimensional space such that the pairwise distances (dissimilarities) between points are best preserved. With this there are many opportunities to enhance the exploration of the space such as visualizing exploration paths and a compass displaying the orientation of the information space.


Originally posted in the Dartmouth College Computer Science Technical Report Series, number TR2020-895.