Machine Learning Methods for Detecting and Monitoring Extremist Information on the Internet

Author:

Mashechkin I. V.,Petrovskiy M. I.,Tsarev D. V.,Chikunov M. N.

Publisher

Pleiades Publishing Ltd

Subject

Software

Reference46 articles.

1. Why big data analytics holds the key to tackling the changing terror threat, J. Adv. Anal. Intell., 2015. http:// www.sas.com/content/dam/SAS/en_us/doc/other1/ iq-q115.pdf.

2. Hankin, C., IDEAS factory – Detecting terrorist activities: Making sense. http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/H023135/1.

3. Nizamani, S. et al., Modeling suspicious email detection using enhanced feature selection, 2013, preprint arXiv 1312.1971.

4. Sheehan, I.S., Assessing and comparing data sources for terrorism research, Evidence-Based Counterterrorism Policy, New York: Springer, 2012, vol. 3, pp. 13–40.

5. Berger, J.M. and Morgan, J., The ISIS Twitter Census, Brookings Project on US Relations with the Islamic World, 2015, no. 20.

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