Sentiment analysis in Uzbek language and new Datasets of Uzbek App reviews for Sentiment Classification
The main contributions of this project are:
-
The creation of the first annotated dataset for sentiment analysis in Uzbek language, obtained from reviews of the top 100 Google Play Store applications used in Uzbekistan. This manually annotated dataset contains 2500 positive and 1800 negative reviews. Furthermore, we have also built a larger dataset by automatically translating (using Google Translate API) an existing English dataset of application reviews. The translated dataset has≈10K positive and≈10K negative app reviews, after manually eliminating themajor machine translation errors by either correctingor removing them completely.
-
The definition of the baselines for sentiment analyses in Uzbek by considering both traditional machine learning methods as well as recent deep learning techniques fed with fastText pre-trained word embeddings. Although all the tested models are relatively accurate and differences between models are small, the neural network models tested do not manage tosubstantially outperform traditional models. We believe that the quality of currently available pre-trained word embeddings for Uzbek is not enough to let deep learning models perform at their full potential.
The results obtained through the research:
Table: Accuracy results with different training and test sets.ManualTT- Manually annotated Training and Test sets.TransTT- Translated Training and Test sets.TTMT- Translated dataset for Training, Annotated dataset for Test set.