title: ÐÐ½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ¸ÑÑÐµÐ¼Ð° Ð´Ð»Ñ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¸ Ð¾ÑÐµÐ½ÐºÐ¸ Ð¾ÑÐ·ÑÐ²Ð¾Ð² Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»ÐµÐ¹ Ð¾ Ð¿ÑÐ¾Ð´ÑÐºÑÐ°Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Information system for researching and evaluating user reviews of products
Creators: name: ÐÐ°Ð½Ð°Ñ, ÐÐ°ÑÐ´Ð¸
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: ÐÐ½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½ÑÐµ ÑÐ¸ÑÑÐµÐ¼Ñ
ÐÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
Ð°Ð½Ð°Ð»Ð¸Ð· Ð¼Ð½ÐµÐ½Ð¸Ð¹
Ð°Ð½Ð°Ð»Ð¸Ð· Ð½Ð°ÑÑÑÐ¾ÐµÐ½Ð¸Ð¹
Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ ÑÐ¿Ð°Ð¼Ð°
Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐ¸ ÑÐ¿Ð°Ð¼Ð°
Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
opinion mining
sentiment analysis
spam detection
spam features
deep learning

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description: The subject of the graduate qualification work is Â«Information system for researching and evaluating user reviews of productsÂ». The given work is devoted studying the tasks of opinion analysis and sentiment analysis, the detection of opinion spam, as well as the creation of spam detection and opinion analysis modules at the review-level and their implementation. The research set the following goals: Demonstrating the impact of spam reviews on the results of the opinion analysis system and the importance of enabling the spam detection module. Creating a spam detection module using features that are extracted from the text of the review, and implementing this system. Analyzing the role of opinion analysis systems in the modern competitive market and various applications of these systems. Creating an opinion analysis system capable of determining the orientation of sentiment in reviews, and implementing this system. Analyzing the obtained test results of the constructed modules based on performance measures. In the course of this work, the importance of opinions as a driving force of human behavior and the market as a whole will be shown, as well as the researched tasks in the field of opinion analysis and various approaches to solving them and the levels of performing opinion analysis will be investigated, and an opinion analysis system will be proposed, including spam detection and sentiment analysis modules on the review-level. Both modules were built and implemented using Python programming language. For this purpose, 2 models were used: a machine learning model for spam detection, and a deep learning model for sentiment analysis. The spam detection module processes the data and extracts all the necessary features from the review- domain before training the model, and the sentiment analysis module processes the data and converts it to numeric values before analysis.In addition, 2 publicly available datasets were used to train machine learning and deep learning models. As a result, these two models were evaluated to demonstrate the effectiveness, reliability and usability of these models along with the proposed approach, as well as their readiness for use in real applications.