社交媒体Twitter中印尼旅游的正确情感分析方法

Cristian Steven, Wella Wella
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引用次数: 6

摘要

社交媒体的发展正在改变人类彼此交流的方式,许多人使用社交媒体,如Twitter来表达意见,经验和其他与他们有关的事情,其中这样的事情通常被称为情绪。社交媒体的概念现在是商业人士关注的焦点,以了解人们对一个产品或一个地方的看法,这些产品或地方将成为一项业务。情感分析或通常也称为意见挖掘是通过实体,事件和拥有的属性对人们的意见,评估和情绪进行计算研究。情绪分析本身最近成为一个热门的研究课题,因为情绪分析可以应用于许多工业部门,其中之一是印度尼西亚的旅游业。为了能够进行情感分析,需要掌握几种技术,例如文本挖掘、机器学习和自然语言处理(NLP)技术,以便能够处理来自社交媒体的大型非结构化数据。常用的方法包括朴素贝叶斯、神经网络、k近邻、支持向量机和决策树。正因为如此,本研究将比较这四种算法,以便一种算法可以用来分析人们对巴厘岛城市的情绪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Right Sentiment Analysis Method of Indonesian Tourism in Social Media Twitter
The growth of social media is changing the way humans communicate with each other, many people use social media such as Twitter to express opinions, experiences and other things that concern them, where things like this are often referred to as sentiments. The concept of social media is now the focus of business people to find out people's sentiments about a product or place that will become a business. Sentiment Analysis or often also called opinion mining is a computational study of people's opinions, appraisal, and emotions through entities, events and attributes owned. Sentiment analysis itself has recently become a popular topic for research because sentiment analysis can be applied in many industrial sectors, one of which is the tourism industry in Indonesia. To be able to do a sentiment analysis requires mastery of several techniques such as techniques for doing text mining, machine learning and natural language processing (NLP) to be able to process large and unstructured data coming from social media. Some methods that are often used include Naive Bayes, Neural Networks, K-Nearest Neighbor, Support Vector Machines, and Decision Tree. Because of this, this research will compare these four algorithms so that an algorithm can be used to analyze people's sentiments towards the city of Bali.
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