I conducted this research with my team in my Network Science course. Our goal was to use Network Science techniques for text processing in Julia, to categorize short text fragments that constitute "unclean data". We found that much of the existing work with Network Science semantic text analysis concerned long documents, and existing work with short fragments was often through machine learning. We wanted to use text vectorization and hamming distance formulas to assess the sentiments of Amazon review titles in an existing dataset. We were able to create neighbors for review titles by their hamming distance from other vectorized texts, with bag of k-gram techniques, and eventually plot visibility clusters in Julia and create meaningful sentiment clusters.