When accessing subscription databases from off-campus, you will be asked to sign in using your campus username and password. If you have any problems accessing library resources from off campus, please contact Tony Lewis or Kayla Reed.
Textual analytics uses computational (often statistical) methods to undertake exploration and analysis of textual data. "Textual data" in this context means the words and characters contained in a textual source, stored in a digital form. Human readers typically read one text at a time. Computers can supplement human reading by helping to identify patterns in much larger datasets.
Textual data analytics can be done using coding languages like Python and R, but it doesn't have to. This guide includes tools that require no programming, some programming, and basic to advanced programming.
If you are curious about or considering textual analytics as a method for your research, keep in mind that there are ethical and legal issues inherent in using others' text. Grinnell College librarians would be happy to discuss these and any other questions that you have about text analytics.
