dc.description.abstracten |
Every day a lot of visitors leave countless reviews about hotels, restaurants, cafes, attractions or other services. In most cases, they set the rate about this service, sometimes they also set the rate about the specific topic if service provides this possibility. However, the main information about user opinion is hidden inside the body of review text. Thereby, in this work, we propose a solution to analyze one or several user reviews, determine sentiments and acquire important characteristics for these reviews. We determine which characteristics were influenced by such reviews. In this case, the proposed solution can detect sentiments from text and classify for positive and negative. Then it acquires top positive and negative phrases, which can explain why the user left such review. Besides, we analyze all reviews about one hotel or just several reviews and summarize the most important positive and negative properties for a specific hotel. |
uk |