An Efficient Model for Sentiment Analysis of Electronic Product Reviews in Vietnamese
This provides enterprises in Vietnam with insights from e-commerce data for better business decisions, but it is incremental as it applies an existing method to a new domain.
The paper tackled sentiment analysis of Vietnamese electronic product reviews, achieving 90.16% accuracy with an inference time of 0.0124 seconds using self-attention neural networks.
In the past few years, the growth of e-commerce and digital marketing in Vietnam has generated a huge volume of opinionated data. Analyzing those data would provide enterprises with insight for better business decisions. In this work, as part of the Advosights project, we study sentiment analysis of product reviews in Vietnamese. The final solution is based on Self-attention neural networks, a flexible architecture for text classification task with about 90.16% of accuracy in 0.0124 second, a very fast inference time.