Kazakh Text Generation using Neural Bag-of-Words Model for Sentiment Analysis

Text generation plays an important role in making decisions in business. Analyzing the consumer’s feedback provides a complete picture of the problem with a definite direction. However, sentimental analyses of reviews in the Kazakh language are not widely cultivated. In this paper, we introduce the Kazakh text generation using the Bag-of-Words model (BoW) models for analyzing the opinions of consumers in social networks. The use of proposed models in natural language processing consists of four stages: data collection, cleaning data, building model, and model evaluation. The proposed BoW model is supported by the platform - Colab notebook and implemented using the python language. Based on experimental results, defined method with higher efficiency as compared to other existing analogs