Text and Data Mining: Explaining the
Relevance
dr. Steven Claeyssens | @sclaeyssens
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
www.delpher.nl www.dbnl.org
http://ngramviewer.kbresearch.nl
https://pimhuijnen.com/2015/12/04/from-keyword-searching-to-concept-mining/
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