Computational Analysis of Catalogue Data

This Carpentries-style lesson introduces people working in catalogue-related roles in galleries, libraries, archives, and museums to analysing catalogue data in AntConc. At the conclusion of the lesson you will understand what the AntConc software does and how to use approaches from computational linguistics for the purposes of examining catalogue data.


To complete this lesson you will need to install AntConc and download the file See Setup for more information.


Setup Download files required for the lesson
00:00 1. Introduction to AntConc What is AntConc? What is corpus linguistics? How can they be combined to analyse catalogue data?
00:05 2. Importing data into AntConc How do I get data into AntConc?
00:15 3. Layout of AntConc How is data organised in AntConc?
How do I access different tools in AntConc?
00:20 4. Settings in AntConc What are the default settings in AntConc?
What changes are recommended for analysing catalogue data?
How can I keep a track of the settings I am using in AntConc?
00:25 5. Word lists What are word lists in AntConc and when would you use it?
How do word lists work in AntConc?
How might I interpret word lists generated from catalogue data?
00:45 6. Searching concordances How can I search in AntConc?
How can I use search to discover features of catalogue data?
01:15 7. Collocates What are collocates?
How do collocates work in AntConc?
What conclusions can be reached based on collocation data?
01:35 8. Next Steps 1: comparing corpora (**not yet developed**) How do can I use AntConc to compare multiple sets of catalogue data?
How can I compare curatorial ‘voice’ to general language?
What are the benefits of comparison?
01:40 9. Next Steps 2: Named Entity Recognition (**not yet developed**) What is Named Entity Recognition (NER)?
How do I apply NER to catalogue data?
How can I use NER to analyse catalogue data in AntConc?
02:00 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.