Journal article | Zeitschriftenartikel

Topic Modeling and Classification of Cyberspace Papers Using Text Mining

The global cyberspace networks provide individuals with platforms to can interact, exchange ideas, share information, provide social support, conduct business, create artistic media, play games, engage in political discussions, and many more. The term cyberspace has become a conventional means to describe anything associated with the Internet and the diverse Internet culture. In fact, cyberspace is an umbrella term that covers all issues occurring through the interaction of information systems and humans over these networks. Deep evaluation of the scientific articles on the cyberspace domain provides concentrated knowledge and insights about major trends of the field. Text mining tools and techniques enable the practitioners and scholars to discover significant trends in a large set of internationally validated papers. This study utilizes text mining algorithms to extract, validate, and analyze 1860 scientific articles on the cyberspace domain and provides insight over the future scientific directions or cyberspace studies.

Topic Modeling and Classification of Cyberspace Papers Using Text Mining

Urheber*in: Sohrabi, Babak; Vanani, Iman Raeesi; Shineh, Mohsen Baranizade

Attribution - NonCommercial 4.0 International

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ISSN
2538-6255
Extent
Seite(n): 103-125
Language
Deutsch
Notes
Status: Veröffentlichungsversion; begutachtet (peer reviewed)

Bibliographic citation
Journal of Cyberspace Studies, 2(1)

Subject
Publizistische Medien, Journalismus,Verlagswesen
Naturwissenschaften
interaktive, elektronische Medien
Naturwissenschaften, Technik(wissenschaften), angewandte Wissenschaften
Internet
interaktive Medien
elektronische Medien
virtuelle Realität
Trend
Algorithmus

Event
Geistige Schöpfung
(who)
Sohrabi, Babak
Vanani, Iman Raeesi
Shineh, Mohsen Baranizade
Event
Veröffentlichung
(when)
2018

DOI
Rights
GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln
Last update
21.06.2024, 4:27 PM CEST

Data provider

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Object type

  • Zeitschriftenartikel

Associated

  • Sohrabi, Babak
  • Vanani, Iman Raeesi
  • Shineh, Mohsen Baranizade

Time of origin

  • 2018

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