Abstract
Literature permeates through almost every facet of our lives, whether through books, magazines, or internet articles. Moreover, every piece of written work contains ideas and opinions that we tend to relate to, accept or disregard, debate over, or enlighten ourselves with. However, the existence of subtle themes that are difficult to discern had inspired us to utilize four machine learning algorithms: Decision Trees, Random Forest, Logistic Regression, and Support Vec- tor Classifier (SVC) to aid in their detection. Trained on the ValueEval data set as a multi- label classification problem, the supervised ma- chine learning models did not perform as well as expected, with F1 metrics hovering from 0.0 to 0.04 for each value. Noting this, the lim- itations and weaknesses of our approach are discussed in our paper.- Anthology ID:
- 2023.semeval-1.302
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2179–2183
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.302
- DOI:
- 10.18653/v1/2023.semeval-1.302
- Cite (ACL):
- Abdul Jawad Mohammed, Sruthi Sundharram, and Sanidhya Sharma. 2023. Friedrich Nietzsche at SemEval-2023 Task 4: Detection of Human Values from Text Using Machine Learning. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 2179–2183, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Friedrich Nietzsche at SemEval-2023 Task 4: Detection of Human Values from Text Using Machine Learning (Mohammed et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/2023.semeval-1.302.pdf