Web Scraping and Text Mining with R Simon Munzert University of - PowerPoint PPT Presentation

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An introduction to Web Scraping and Text Mining with R Simon Munzert University of Konstanz October 2014 Web Scraping with R Simon Munzert An introduction to Web Scraping and Text Mining with R Simon Munzert University of Konstanz

An introduction to Web Scraping and Text Mining with R Simon Munzert University of Konstanz October 2014 Web Scraping with R Simon Munzert
An introduction to Web Scraping and Text Mining with R Simon Munzert University of Konstanz October 2014 Web Scraping with R Simon Munzert
Session overview Session Topics Book chapter Fri, 10/03 Scraping static content using. . . . . . XML/HTML parsing 3 . . . XPath/SelectorGadget 4 . . . Regular expressions 8 Fri, 10/17 Scraping dynamic content + APIs using. . . . . . JSON 3 . . . APIs 9 . . . AJAX 6 . . . Selenium 9 What I won’t cover: internals of HTTP, complex parsing techniques, OAuth, databases, advanced workflow Web Scraping with R Simon Munzert
First: ask questions! No matter what. . . Web Scraping with R Simon Munzert
Web scraping. What? Why? The World Wide Web is full of various kinds of new data, e.g.: • open government data • search engine data • services that track social behavior Web scraping A.k.a. screen scraping, web harvesting. Computer-aided collection of predominantly unstructured data (e.g., from HTML code) Practical arguments • financial resources are sparse • . . . and so is our time • reproducibility Web Scraping with R Simon Munzert

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