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所在平台: Udemy |
课程主页: https://www.udemy.com/course/r-social-media-mining-scraping-with-twitter/
课程评论：没有评论
课程名称：文本挖掘、网络爬虫与R语言情感分析 课程概述：本课程面向高级R用户，旨在扩展您的R工具箱，特别是对社交媒体情感分析感兴趣的学习者。如果您希望了解如何获取和使用Twitter数据进行R分析，系统性地查找与搜索词相关的关键词，并制作如词云等文本数据可视化图表，那么这个课程将非常适合您！ 在课程中，我们将以Twitter数据作为示例数据集，逐步介绍如何处理社交媒体数据的文本分析过程。您将学习可用于社交媒体分析的R包，了解如何抓取Twitter数据并将其导入R环境。接下来，您将掌握如何筛选、清洗和构建文本语料库，然后使用词云和树状图对文本数据进行可视化。最后，我们将进行完整的情感分析，利用常用的词典进行分析。 每一个环节都有相应的练习，让您能够检验学习效果，并应用所学知识。根据R教程的教学原则，课程的每个部分都配备了练习，以提升学习体验。您还可以下载每个环节的代码PDF，便于独立尝试所介绍的代码。 注意：Twitter的商标归Twitter, Inc或其关联公司所有，包括“TWITTER”、“TWEET”、“RETWEET”和Twitter徽标。
Are you an advanced R user, looking to expand your R toolbox? Are you interested in social media sentiment analysis? Do you want to learn how you can get and use Twitter data for your R analysis? Do you want to learn how you can systematically find related words (keywords) to a search term using Twitter and R? Are you interested in creating visualizations like wordclouds out of text data? Do you want to learn which R packages you can use for web scraping and text analysis purposes? If YES came to your mind to some of those points - this course might be tailored towards your needs! This course will teach you anything you need to know about how to handle social media data in R. We will use Twitter data as our example dataset. During this course we will take a walk through the whole text analysis process of Twitter data. At first you will learn which packages are available for social media analysis. You will learn how to scrape social media (Twitter) data and get it into your R session. After that we will filter, clean and structure our text corpus. The next step is the visualization of the text data via wordclouds and dendrograms. And in the last section we will do a whole sentiment analysis by using a common word lexicon. All of those steps are accompanied by exercise sessions so that you can check if you can put the information to work. According to the teaching principles of R Tutorials every section is enforced with exercises for a better learning experience. You can download the code pdf of every section to try the presented code on your own. Disclaimer required by Twitter: 'TWITTER, TWEET, RETWEET and the Twitter logo are trademarks of Twitter, Inc or its affiliates.'
