The Hidden Shape of Data: Topological Data Analysis for Anxiety Detection in Text
| dc.contributor.advisor | Metsis, Vangelis | |
| dc.contributor.author | Byers, Morgan | |
| dc.date.accessioned | 2021-06-04T17:22:41Z | |
| dc.date.available | 2021-06-04T17:22:41Z | |
| dc.date.issued | 2021-05 | |
| dc.description.abstract | A significant portion of the veteran population experiences post-traumatic stress disorder, or PTSD, as a result of their service. This is often accompanied by social anxiety disorder. In particular, student veterans are especially vulnerable as they struggle to integrate into a college lifestyle. In an effort to improve the support systems available for student veterans, we employ approaches from topological data analysis, an emerging area of research, to anxiety detection in text. Our models provide a tool to support psychologists and social workers in treating social anxiety.The results detailed in this paper could also have broader impacts in fields such as pedagogy and public health. | |
| dc.description.department | Honors College | |
| dc.format | Text | |
| dc.format.extent | 28 pages | |
| dc.format.medium | 1 file (.pdf) | |
| dc.identifier.citation | Byers, M. (2021). The hidden shape of data: Topological data analysis for anxiety detection in text (Unpublished thesis). Texas State University, San Marcos, Texas. | |
| dc.identifier.uri | https://hdl.handle.net/10877/13762 | |
| dc.language.iso | en | |
| dc.subject | machine learning | |
| dc.subject | topological data analysis | |
| dc.subject | persistent homology | |
| dc.subject | natural language processing | |
| dc.subject | text analysis | |
| dc.subject | topology | |
| dc.subject | Honors College | |
| dc.title | The Hidden Shape of Data: Topological Data Analysis for Anxiety Detection in Text | |
| thesis.degree.department | Honors College | |
| thesis.degree.discipline | Computer Science | |
| thesis.degree.grantor | Texas State University | |
| txstate.documenttype | Honors Thesis |