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2021 | OriginalPaper | Chapter

Diachronic Linguistic Periodization of Temporal Document Collections for Discovering Evolutionary Word Semantics

Authors : Yijun Duan, Adam Jatowt, Masatoshi Yoshikawa, Xin Liu, Akiyoshi Matono

Published in: Towards Open and Trustworthy Digital Societies

Publisher: Springer International Publishing

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Abstract

Language is our main communication tool. Deep understanding of its evolution is imperative for many related research areas including history, humanities, social sciences, etc. To this end, we are interested in the task of segmenting long-term document archives into naturally coherent periods based on the evolving word semantics. There are many benefits of such segmentation such as better representation of content in long-term document collections, and support for modeling and understanding semantic drift. We propose a two-step framework for learning time-aware word semantics and periodizing document archive. Encouraging effectiveness of our model is demonstrated on the New York Times corpus spanning from 1990 to 2016.

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next chapter Joint Model Using Character and Word Embeddings for Detecting Internet Slang Words
Footnotes
1
The overall vocabulary V is the union of vocabularies of each time unit, and thus it is possible for some \(w \in V\) to not appear at all in some time units. This includes emerging words and dying words that are typical in real-world news corpora.
 
2
These sections are Arts, Business, Fashion & Style, Health, Home & Garden, Real Estate, Science, Sports, Technology, U.S., World.
 
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Metadata
Title
Diachronic Linguistic Periodization of Temporal Document Collections for Discovering Evolutionary Word Semantics
Authors
Yijun Duan
Adam Jatowt
Masatoshi Yoshikawa
Xin Liu
Akiyoshi Matono
Copyright Year
2021
Book
Towards Open and Trustworthy Digital Societies

Print ISBN: 978-3-030-91668-8

Electronic ISBN: 978-3-030-91669-5

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-91669-5_1

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