Sentiment Analysis Using Lexicon Based Approach

Vijendra Singh, Gurdeep Singh, Priyanka Rastogi, Devanshi Deswal
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引用次数: 11

Abstract

With increasing easy access to internet there is an emergence of e-commerce and social media portals. There is a huge surge in the production of the human sentiments in form of customer reviews and feedback on these platforms. As per a survey approximately 2,500,000 Terabytes of data is created every day and 90% of the data which exist today has been created in the past 2 years only. This huge amount of data created is called big data. The main problem associated with this huge data is that it is in unstructured form. So, to gain information, first we must process it using various methods. This paper proposes a Human sentiment analysis model (HSAM), which can perform sentiment analysis on any given data set.
基于词典的情感分析方法
随着互联网接入越来越容易,电子商务和社交媒体门户网站也出现了。在这些平台上,以客户评论和反馈的形式产生的人类情感激增。根据一项调查,每天大约有2,500,000 tb的数据被创建,今天存在的90%的数据是在过去两年内创建的。这种大量的数据被称为大数据。与这些庞大数据相关的主要问题是它们是非结构化的形式。因此,为了获得信息,首先我们必须使用各种方法来处理它。本文提出了一种人类情感分析模型(HSAM),该模型可以对任意给定的数据集进行情感分析。
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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