Sentiment Analysis of Yelp using Advanced V Model

A. Shaout, Udit Gami
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Abstract

Yelp is a business review site that helps people find relevant places, based on the informed opinions of its users. It uses a five-point star rating system with user reviews. The main aim of the paper is to analyze sentiments on the reviews and devise a new five-scale sentiment rating to match it to the star rating that the user provided. Following the n-gram approach, this paper analyzes the adjective and adverbs occurring sequences and determines the trend or pattern of occurrence. After calculating a weighted score for each review, users’ ratings are predicted by treating multi class classification using different classifiers. The objective of the research in this paper is to try and determine how accurate the users are, in giving the ratings by comparing their star based on the calculated results.
基于高级V模型的Yelp情感分析
Yelp是一个商业评论网站,帮助人们根据用户的意见找到相关的地方。它使用带有用户评论的五星评级系统。本文的主要目的是分析评论上的情绪,并设计一个新的五级情绪评级,将其与用户提供的星级评级相匹配。本文采用n-gram方法,分析形容词和副词的发生顺序,确定其发生的趋势或模式。在计算每个评论的加权分数后,通过使用不同的分类器处理多类分类来预测用户的评分。本文研究的目的是试图确定用户在给出评级时的准确性,根据计算结果比较他们的星级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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