社交媒体平台情感分析技术的文献综述

Samarth Garg, Divyansh Singh Panwar, Aakansha Gupta, R. Katarya
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引用次数: 4

摘要

情感分析是自然语言处理的一个活跃领域,它提取人类的态度和情感。随着社交媒体的发展,越来越多的人使用在线平台,如Twitter、Facebook、youtube等来表达自己的观点。推特被认为是表达个人观点最纯粹的平台。几乎所有来自不同背景的人都使用twitter。因此,研究民意成为当务之急。这为我们提供了有价值的信息,帮助组织和政府考虑大众舆论,并据此做出更好的决策。在这篇综述论文中,提出了自然语言处理(NLP)子领域的广泛而详尽的指南,重点是对twitter数据集的情感分析。它强调了分析市场情绪的三种主要方法。我们总结并比较了使用twitter数据集的不同研究人员在情感分析领域选择的不同指标的方法。在这一领域有如此多的活跃工作,这篇综述文章将有助于所有未来的研究者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Literature Review On Sentiment Analysis Techniques Involving Social Media Platforms
Sentiment analysis refers to the active field of Natural language processing that extracts the attitude and emotion of a human being. With the growth of social media, more people are using online platforms such as Twitter, Facebook, Y ouTube, etc. to express their opinions. Twitter is considered to be the purest platform to express one's views. Mostly all personalities from diverse backgrounds use twitter. Therefore, it becomes a need of the hour to study public opinion. This provides us valuable information and helps organizations and governments to contemplate mass public opinion and take better decisions accordingly. In this review paper, an extensive and exhaustive guide to the subfield of Natural language processing (NLP), focusing precisely on sentiment analysis on twitter dataset, has been presented. It highlights three main approaches to analyze the sentiment. We have summarized and compared the approaches on different metrics opted by various researchers in the field of sentiment analysis using the twitter dataset. With so much active work in this field, this review paper would assist all future researchers.
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