Topic Modeling in Theory and Practice
| dc.contributor.advisor | Van Durme, Benjamin | |
| dc.contributor.committeeMember | Dredze, Mark | |
| dc.contributor.committeeMember | Yarowsky, David | |
| dc.creator | May, Chandler Camille | |
| dc.creator.orcid | 0000-0002-1655-6527 | |
| dc.date.accessioned | 2022-07-25T17:55:22Z | |
| dc.date.available | 2022-07-25T17:55:22Z | |
| dc.date.created | 2022-05 | |
| dc.date.issued | 2022-03-28 | |
| dc.date.submitted | May 2022 | |
| dc.date.updated | 2022-07-25T17:55:23Z | |
| dc.description.abstract | Topic models can decompose a large corpus of text into a relatively small set of interpretable themes or topics, potentially enabling a domain expert to explore and analyze a corpus more efficiently. However, in my work, I have found that theories put forth by topic modeling research are not always borne out in practice. In this dissertation, I use case studies to explore four theories of topic modeling. While these theories are not explicitly stated, I show that they are communicated implicitly, some within an individual study and others more diffusely. I show that this implicit knowledge fails to hold in practice in the settings I consider. While my work is confined to topic modeling research and moreover concentrated on the latent Dirichlet allocation topic model, I argue that these kinds of gaps may pervade scientific research and present an obstacle to improving the diversity of the research community. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://jhir.library.jhu.edu/handle/1774.2/67095 | |
| dc.language.iso | en_US | |
| dc.publisher | Johns Hopkins University | |
| dc.publisher.country | USA | |
| dc.subject | natural language processing | |
| dc.subject | machine learning | |
| dc.subject | artificial intelligence | |
| dc.subject | topic modeling | |
| dc.subject | reproducibility | |
| dc.title | Topic Modeling in Theory and Practice | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | Computer Science | |
| thesis.degree.discipline | Computer Science | |
| thesis.degree.grantor | Johns Hopkins University | |
| thesis.degree.grantor | Whiting School of Engineering | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Ph.D. |