Publication: Topic modeling and sentiment analysis on online learning experience during the pandemic
| dc.contributor.author | Ugay, Herowin B. | |
| dc.contributor.author | Canlas, Mhay V. | |
| dc.contributor.author | Laceste, Daniel Angelo R. | |
| dc.contributor.author | Mendigoria, John Christopher A. | |
| dc.date.accessioned | 2025-10-10T06:32:28Z | |
| dc.date.available | 2025-10-10T06:32:28Z | |
| dc.date.issued | 2023-04 | |
| dc.description | Full text. | |
| dc.description.abstract | In this study, the researchers assess students' opinions towards online learning through sentiment analysis. To achieve this, the Support Vector Machine technique was applied to identify the hyperplane that separates students' sentiments into positive and negative classes. The user's thoughts and experiences with online learning were obtained, preprocessed, sentimentally assessed, and then interpreted. In addition, topic modeling was performed using the K-Means clustering algorithm to provide a cost-effective and efficient approach to sentiment analysis. The specific objectives of this study are to determine the preprocessing techniques, train the sentiment analysis model, evaluate the model's performance in terms of accuracy, precision, recall, and F J -Score, and to perform topic model analysis. Thefindings from this study will provide useful information for academic institutions and educators to improve their online learning strategies. | |
| dc.identifier.citation | Ugay, H. B., Canlas, M. V., Laceste, D. A. R., & Mendigoria, J. C. A. (2023) Topic modeling and sentiment analysis on online learning experience during the pandemic [Unpublished Undergraduate thesis]. Don Mariano Marcos Memorial State University - South La Union Campus, Agoo, La Union. | |
| dc.identifier.uri | https://lakasa.dmmmsu.edu.ph/handle/123456789/520 | |
| dc.language.iso | en_US | |
| dc.publisher | Don Mariano Marcos Memorial State University - South La Union Campus | |
| dc.sdg | SDG 9 | |
| dc.title | Topic modeling and sentiment analysis on online learning experience during the pandemic | |
| dc.type | Thesis | |
| dspace.entity.type | Publication |