Abstract
The purpose of this paper is to develop a hybrid model Ukrainian language sentiment analyzer, which should improve the accuracy of the mood definition to expand the Ukrainian language among the instruments on the market. The object of research is the processes of determining the language of the text and predicting its sentiment score. The subject of the study is Ukrainian comments posted by Google Maps users. The following text categories are taken into account: food, hotels, museums, and shops. The new method was built as an ensemble of support vector machine, logistic regression, and XGBoost, in combination with a rule-based algorithm. The practical use of the algorithm makes it possible to analyze the Ukrainian text in accordance with the category with the visualization of the research results. The accuracy of the proposed method is bigger than 0.88 in the worst case. The mining procedure of the positive and negative sides of service providers based on users’ feedback is developed. It allows electronics business to make improvements based on frequent positive and negative words.
Highlights
Emotions are an integral part of our mental activity and play a key role in communication and decision-making processes
The aim of the paper is to develop a method of sentimental analysis of Ukrainian text due to the problem with corpus absent, poor libraries and tools for this language
To improve the accuracy of text analysis, it is proposed to create a hybrid model as a combination of machine learning models with a rule-based algorithm
Summary
Emotions are an integral part of our mental activity and play a key role in communication and decision-making processes. In addition to analyzing customer sentiment, the system owners can check the work of their employees, for instance, in support or call centers Processing knowledge from such a large amount of unstructured information is an extremely difficult task, because the content of today’s Internet is quite suitable for human perception, but remains. Despite a large number of text processing and analysis tools, there are only a few which support Ukrainian text analysis These are just small projects with created libraries, which can be used only by developers, not by ordinary users. The aim of the paper is to develop a method of sentimental analysis of Ukrainian text due to the problem with corpus absent, poor libraries and tools for this language. The last section concludes this paper, containing the probable decision of the appraisal technique
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