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  • Correction
  • Open Access

Correction to: Detection and classification of social media-based extremist affiliations using sentiment analysis techniques

  • 1Email author,
  • 2,
  • 3 and
  • 4
Human-centric Computing and Information Sciences20199:27

https://doi.org/10.1186/s13673-019-0189-2

  • Published:

The original article was published in Human-centric Computing and Information Sciences 2019 9:24

Correction to: Hum Cent Comput Inf Sci (2019) 9:24 https://doi.org/10.1186/s13673-019-0185-6

In the original publication of this article [1], the Acknowledgements and Funding section in Declarations need to be revised. The updated note should be:

This project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under Grant No. G:277-830-1439. The authors, therefore, acknowledge with thanks DSR for technical and financial support.

Notes

Declarations

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Faculty of Computing and Information Technology at Rabigh (FCITR), King Abdul Aziz University (KAU), Jeddah, Kingdom of Saudi Arabia
(2)
Institute of Computing and Information Technology, Gomal University, Dera Ismail Khan (KP), Pakistan
(3)
Department of Information Systems, Faculty of Computing and Information Technology (FCIT), King Abdul Aziz University (KAU), Jeddah, Kingdom of Saudi Arabia
(4)
Department of Computing, University of Bradford, Bradford, UK

Reference

  1. Ahmad S, Asghar MZ, Alotaibi FM, Awan I (2019) Detection and classification of social media-based extremist affiliations using sentiment analysis techniques. Hum Cent Comput Inf Sci 9:24. https://doi.org/10.1186/s13673-019-0185-6 View ArticleGoogle Scholar

Copyright

© The Author(s) 2019

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