Visions and open challenges for a knowledge-based culturomics
Journal article, 2015

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.

Statistical analysis

eInfrastructure

Culturomics

Natural language processing

eScience

Knowledge-based analysis

Temporal text analysis

Digital humanities

Author

Nina Tahmasebi

University of Gothenburg

Lars Borin

University of Gothenburg

Gabriele Capannini

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Devdatt Dubhashi

Chalmers, Computer Science and Engineering (Chalmers), Computing Science (Chalmers)

Peter Exner

Lunds Universitet

Markus Forsberg

University of Gothenburg

Gerhard Gossen

L3S Research Center

Fredrik Johansson

Chalmers, Computer Science and Engineering (Chalmers), Computing Science (Chalmers)

Richard Johansson

University of Gothenburg

Mikael Kågebäck

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Olof Mogren

Chalmers, Computer Science and Engineering (Chalmers), Computing Science (Chalmers)

Pierre Nugues

Lunds Universitet

Thomas Risse

L3S Research Center

International Journal on Digital Libraries

1432-5012 (ISSN)

Vol. 15 169-187

Areas of Advance

Information and Communication Technology

Subject Categories

Language Technology (Computational Linguistics)

Computer Science

DOI

10.1007/s00799-015-0139-1