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所在平台: Udemy |
课程主页: https://www.udemy.com/course/analysing-tweets-using-r/
课程评论：没有评论
**课程名称：** 使用R分析推特数据 **课程概述：** 随着全球每天超过5亿条推文的产生，Twitter蕴藏着巨大的数据宝藏。本课程将教授您如何利用R语言收集、分析和提取推特数据中的信息。您将学习： * **数据收集：** 如何使用R语言从Twitter抓取数据。 * **基础分析：** 如何对收集到的推特数据进行基本的数据分析。 * **情感提取：** 如何从推文中挖掘和分析用户表达的情感。 本课程还将介绍分析Twitter数据所需的API，例如Google Maps API。 **先决条件：** * **R编程基础：** 建议学员具备R编程语言的基础知识。 * **Twitter开发者账号：** 强烈建议创建Twitter开发者账号，以充分利用课程内容。课程将提供创建账号的详细步骤。但即使没有开发者账号，学员也能学习课程内容，只是可获取的数据量会受限，可能影响分析的广度。 **潜在优势：** 即使您偏好使用Python等其他编程语言，本课程也能帮助您理解分析Twitter数据的关键概念和技术，并将这些知识迁移到您熟悉的语言中。
People around the globe make over 500 million tweets per day. So, one can only imagine the sheer volume of data available with Twitter. This data is a treasure trove of information. However, one needs to know how to gather this data and then conduct the needed analysis.This course provides all the information regardingHow to gather data from Twitter using R ProgrammingHow to conduct basic analysis of the data gathered from TwitterHow to extract the Emotion expressed in the Tweets gatheredThe course also discusses associated APIs required for analysing Twitter data like Google Maps API.To take full advantage of the course, it will be required to create a developer account with Twitter. All the necessary steps for getting a Twitter Developer Account is provided in the course. However, it must be noted that it is the discretion of Twitter whether they will grant a Twitter Developer account against an application. Nevertheless, all the contents of the course can be followed and understood without a Twitter Developer account. Only difference will be that the data extracted from Twitter will be restricted. With limited data, the analysis possible will be limited.We will use R Programming throughout this course. Thus, this course requires that the participants are conversant with R Programming.If you prefer any other programming language (like. Python, etc.), then you can use this course to learn all the nuances of analysing Twitter Data and apply the same in programming in your language of your preference.
