Here are weblinks to provide additional resources so that you can complete the below exercises:
Click on the following links, which will open in a new window.
Exercise 1: Basic queries using the Twitter Search API via the web interface
We will begin our exploration of Twitter data as geodata by conducting some simple searches directly from the Twitter web interface. The simplest search operators allow us to examine recent tweets that include place names as part of the text.
trendsmap.com shows you the latest trends from Twitter, for anywhere in the world.
Exercise 2: Using TAGS for querying and storing Twitter search results
If you do not yet have access to Google Sheets online spreadsheet software, you can get started at www.google.com/sheets/about/.
The Twitter Archiving Google Spreadsheet (TAGS) is a tool developed by Martin Hawksey for Twitter data collection and visualization. While listed as a “hobby project” on Hawksey’s informational page about the tool, it nevertheless provides an easy-to-use but powerful means for organizing Twitter search results.
Exercise 3: Using the R programming language for accessing Twitter data
While many consider it to be software for statistical analysis, R is actually a robust programming language that is suitable for a wide range of computational tasks. An implementation of the S language developed at Bell Laboratories, R is a free and open source software environment that emerged in the late 1990s and has grown to become one of the most popular programming languages for data science and analysis today.
For more detailed examples and documentation you should visit the main R website at https://cran.r-project.org/. A good overview and introduction manual can be found at cran.r-project.org/doc/manuals/r-release/R-intro.html.
For more information on the twitteR package, go to https://cran.r-project.org/web/packages/twitteR/twitteR.pdf
For more information on the streamR package, go to https://cran.r-project.org/web/packages/streamR/streamR.pdf