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This book presents established and state-of-the-art methods in
Language Technology (including text mining, corpus linguistics,
computational linguistics, and natural language processing), and
demonstrates how they can be applied by humanities scholars working
with textual data. The landscape of humanities research has
recently changed thanks to the proliferation of big data and large
textual collections such as Google Books, Early English Books
Online, and Project Gutenberg. These resources have yet to be fully
explored by new generations of scholars, and the authors argue that
Language Technology has a key role to play in the exploration of
large-scale textual data. The authors use a series of illustrative
examples from various humanistic disciplines (mainly but not
exclusively from History, Classics, and Literary Studies) to
demonstrate basic and more complex use-case scenarios. This book
will be useful to graduate students and researchers in humanistic
disciplines working with textual data, including History, Modern
Languages, Literary studies, Classics, and Linguistics. This is
also a very useful book for anyone teaching or learning Digital
Humanities and interested in the basic concepts from computational
linguistics, corpus linguistics, and natural language processing.
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