Towards Cultural-Scale Models of Full Text
For the past year, Colin and I have been on a HathiTrust Advanced Collaborative Support (ACS) Grant. This project has examined how topic models differ between library subject areas. For example, some areas may have a “canon” meaning that a low number of topics selects the same themes, no matter what the corpus size is. In contrast, still emerging fields may not agree on the overall thematic structure. We also looked at how sample size affects these models. We’ve uploaded the initial technical report to the arXiv:
Towards Cultural Scale Models of Full Text
Jaimie Murdock, Jiaan Zeng, Colin Allen
In this preliminary study, we examine whether random samples from within given Library of Congress Classification Outline areas yield significantly different topic models. We find that models of subsamples can equal the topic similarity of models over the whole corpus. As the sample size increases, topic distance decreases and topic overlap increases. The requisite subsample size differs by field and by number of topics. While this study focuses on only five areas, we find significant differences in the behavior of these areas that can only be investigated with large corpora like the Hathi Trust.