An adaptive COVID 19 sentiment analysis model by coupling textual lexicon and transfer learning
|Stipend||RM2,800.00 (T & C applies)
|Education Level||Masters in Computer Science/Information Technology/ Computer Technology|
|Specific Skills / Knowledge Required||Computer Science/Information Technology or relevant technology background is preferable|
|Job Description||1. To compare the performance and shortcomings on the classification performance of state-of-the-art Deep Learning Transformers on COVID 19 tweet datasets.|
2. To investigate the traditional multi-label classification model (positive/negative) and a multi-class classification model to reflect the emotions rather than the abstract sentiment polarity.
3. To develop an emotion classification model that combines textual lexicon and transfer learning.
|How to Apply||If you are interested, please contact Dr. Ramesh Kumar Ayyasamy at email@example.com|