A lightweight approach for user and keyword classification in controversial topics

Zareie, A., Bontcheva, K. orcid.org/0000-0001-6152-9600 and Scarton, C. orcid.org/0000-0002-0103-4072 (2025) A lightweight approach for user and keyword classification in controversial topics. In: Maria Aiello, L., Chakraborty, T. and Gaito, S., (eds.) Social Networks Analysis and Mining (ASONAM 2024). The 16th International Conference on Advances in Social Networks Analysis and Mining - ASONAM-2024, 02-05 Sep 2024, Rende, Italy. Lecture Notes in Computer Science, 15212 (1). Springer Nature Switzerland , pp. 243-253. ISBN 9783031785375

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Maria Aiello, L.
  • Chakraborty, T.
  • Gaito, S.
Copyright, Publisher and Additional Information:

© 2024 The Authors. Except as otherwise noted, this author-accepted version of a paper published in Social Networks Analysis and Mining is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: Users Classification; Keyword Classification; Stance Detection; Random Walk
Dates:
  • Published: 25 January 2025
  • Published (online): 25 January 2025
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 07 Mar 2025 08:29
Last Modified: 07 Mar 2025 08:31
Status: Published
Publisher: Springer Nature Switzerland
Series Name: Lecture Notes in Computer Science
Refereed: Yes
Identification Number: 10.1007/978-3-031-78538-2_21
Related URLs:
Open Archives Initiative ID (OAI ID):

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