Real Time Sentiment Analysis

Sandip Palit, Soumadip Ghosh
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引用次数: 4

Abstract

Data is the most valuable resource. We have a lot of unstructured data generated by the social media giants Twitter, Facebook, and Google. Unfortunately, analytics on unstructured data cannot be performed. As the availability of the internet became easier, people started using social media platforms as the primary medium for sharing their opinions. Every day, millions of opinions from different parts of the world are posted on Twitter. The primary goal of Twitter is to let people share their opinion with a big audience. So, if the authors can effectively analyse the tweets, valuable information can be gained. Storing these opinions in a structured manner and then using that to analyse people's reactions and perceptions about buying a product or a service is a very vital step for any corporate firm. Sentiment analysis aims to analyse and discover the sentiments behind opinions of various people on different subjects like commercial products, politics, and daily societal issues. This research has developed a model to determine the polarity of a keyword in real time.
实时情绪分析
数据是最有价值的资源。我们有很多由社交媒体巨头Twitter、Facebook和b谷歌生成的非结构化数据。不幸的是,无法执行对非结构化数据的分析。随着互联网的普及,人们开始使用社交媒体平台作为分享意见的主要媒介。每天,数以百万计的来自世界各地的观点被发布在推特上。Twitter的主要目标是让人们与更多的人分享他们的观点。因此,如果作者能够有效地分析推文,就可以获得有价值的信息。以一种结构化的方式存储这些意见,然后用它来分析人们对购买产品或服务的反应和看法,这对任何一家公司来说都是非常重要的一步。情感分析的目的是分析和发现不同的人对不同的主题,如商业产品,政治和日常社会问题的意见背后的情绪。本研究开发了一个实时确定关键词极性的模型。
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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