Sentiment Analysis on Zomato Reviews

Rahul Gupta, Syed Sameer, Harsha Muppavarapu, M. Enduri, Satish Anamalamudi
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引用次数: 3

Abstract

The impact of online reviews on restaurants has reached to unprecedented level where vast number of people are checking posted opinions/reviews prior to ordering their food deliveries. The two main concepts used in the online reviews are sentiment analysis and exploratory data analysis (EDA). The goal of sentimental analysis is to determine whether the given data is positive, negative or neutral. It can help brands to determine how their product is perceived by their clientele. Sentiment analysis, otherwise known as opinion mining, works thanks to natural language processing and machine learning algorithms, to automatically determine the emotional tone behind online conversations. Sentiment analysis mainly relies on the keywords. The overall analysis is made on the data that has been reviewed on Zomato. Most restaurants available on the applications are established ones, hence we get a good idea regarding the restaurants of Hyderabad. Exploratory data analysis (EDA) is a term for certain kinds of initial analysis and findings done with data sets, usually early in an analytical process.
Zomato评论的情感分析
网上评论对餐馆的影响已经达到了前所未有的程度,很多人在点餐前都会查看网上的评论。在线评论中使用的两个主要概念是情感分析和探索性数据分析(EDA)。情感分析的目标是确定给定的数据是积极的,消极的还是中性的。它可以帮助品牌确定客户对其产品的看法。情感分析,也被称为意见挖掘,利用自然语言处理和机器学习算法,自动确定在线对话背后的情感基调。情感分析主要依赖于关键词。整体分析是在Zomato上审查的数据上进行的。应用程序上提供的大多数餐馆都是老牌餐馆,因此我们对海德拉巴的餐馆有了一个很好的了解。探索性数据分析(EDA)是对数据集进行的某些类型的初始分析和发现的术语,通常在分析过程的早期进行。
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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