Does network complexity help organize Babel's library?
This work addresses text categorization for linguistics or computational analysis, but it appears incremental as it builds on existing complex network methods without clear new breakthroughs.
The study analyzed texts using complex network theory, linking words by co-occurrence to find that topological properties can categorize texts as meaningful or senseless, with some properties tied to word frequency and grammar.
In this work, we study properties of texts from the perspective of complex network theory. Words in given texts are linked by co-occurrence and transformed into networks, and we observe that these display topological properties common to other complex systems. However, there are some properties that seem to be exclusive to texts; many of these properties depend on the frequency of words in the text, while others seem to be strictly determined by the grammar. Precisely, these properties allow for a categorization of texts as either with a sense and others encoded or senseless.