Dr. Steven Claeyssens discusses the relevance of text and data mining, emphasizing its evolution over 200 years of data collection and digitization. The document highlights the use of computational techniques to analyze large text corpora, enabling scholars to identify patterns in cultural and societal contexts. This approach facilitates new insights into history and human behavior through the examination of networks, concepts, and ideas over time.

1. Text and Data Mining: Explaining the Relevance
dr. Steven Claeyssens | @sclaeyssens

3. Text and data
= result of
more than 200 years of collecting
over 30 years of digitisation
almost 10 years of collecting born-digital
= machine readable, mostly textual
= structured or semi-structured
= legally as open as possible

5. www.delpher.nl www.dbnl.org

6. http://ngramviewer.kbresearch.nl

7. https://pimhuijnen.com/2015/12/04/from-keyword-searching-to-concept-mining/

8. Text and Data Mining
= using text corpora in bulk as complex (‘biggish’, structured and semi-structured) data
= using computational techniques (IR, NLP, ML, NER, vector space models, …) to derive information
by computer scientists and (digital) humanities scholars
e.g. historians: track actors (networks), concepts (semantic fields) and ideas over space and time
=> identifying patterns and needles (longue durée and microhistory)
= new ways to help us understand culture, society, humanity

9. Any questions?
www.kb.nl/dataservices
www.kb.nl/dh
steven.claeyssens@kb.nl
@sclaeyssens

10. Any questions?
www.kb.nl/dataservices
www.kb.nl/dh
steven.claeyssens@kb.nl
@sclaeyssens