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Visions and open challenges for a knowledge-based culturomics

Journal article
Authors Nina Tahmasebi
Lars Borin
Gabriele Capannini
Devdatt Dubhashi
Peter Exner
Markus Forsberg
Gerhard Gossen
Fredrik Johansson
Richard Johansson
Mikael Kågebäck
Olof Mogren
Pierre Nugues
Thomas Risse
Published in International Journal on Digital Libraries
Volume 15
Issue 2-4
Pages 169-187
ISSN 1432-5012
Publication year 2015
Published at Department of Swedish
Pages 169-187
Language en
Links dx.doi.org/10.1007/s00799-015-0139-...
https://gup.ub.gu.se/file/204693
Keywords Culturomics, Statistical analysis, Knowledge-based analysis, Temporal text analysis, Digital humanities, eScience, eInfrastructure, Natural language processing
Subject categories Computer Science, Language Technology (Computational Linguistics)

Abstract

The concept of culturomics was born out of the availability of massive amounts of textual data and the interest to make sense of cultural and language phenomena over time. Thus far however, culturomics has only made use of, and shown the great potential of, statistical methods. In this paper, we present a vision for a knowledge-based culturomics that complements traditional culturomics. We discuss the possibilities and challenges of combining knowledge-based methods with statistical methods and address major challenges that arise due to the nature of the data; diversity of sources, changes in language over time as well as temporal dynamics of information in general. We address all layers needed for knowledge-based culturomics, from natural language processing and relations to summaries and opinions.

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