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020 _a9783030412517
_9978-3-030-41251-7
024 7 _a10.1007/978-3-030-41251-7
_2doi
050 4 _aQA76.9.A25
072 7 _aUR
_2bicssc
072 7 _aUTN
_2bicssc
072 7 _aCOM053000
_2bisacsh
072 7 _aUR
_2thema
072 7 _aUTN
_2thema
082 0 4 _a005.8
_223
245 1 0 _aOpen Source Intelligence and Cyber Crime
_h[electronic resource] :
_bSocial Media Analytics /
_cedited by Mohammad A. Tayebi, Uwe Glässer, David B. Skillicorn.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aV, 251 p. 88 illus., 69 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Social Networks,
_x2190-5436
505 0 _aChapter1. Studying the Weaponization of Social Media: Case Studies of Anti-NATO Disinformation Campaigns -- Chapter2. Cognitively-Inspired Inference for Malware Task Indentation -- Chapter3. Beyond the ‘Silk Road’: Assessing Illicit Drug Marketplaces on the Public Web -- Chapter4. Protecting the Web from Misinformation -- Chapter5. Social Media for Mental Health: Data, Methods, and Findings -- Chapter6. Twitter Bots and the Swedish Election -- Chapter7. Automated Text Analysis for Intelligence Purposes: A Psychological Operations Case Study -- Chapter8. You are Known by Your Friends: Leveraging Network Metrics for Bot Detection in Twitter -- Chapter9. Inferring Systemic Nets with Applications to Islamist Forums.
520 _aThis book shows how open source intelligence can be a powerful tool for combating crime by linking local and global patterns to help understand how criminal activities are connected. Readers will encounter the latest advances in cutting-edge data mining, machine learning and predictive analytics combined with natural language processing and social network analysis to detect, disrupt, and neutralize cyber and physical threats. Chapters contain state-of-the-art social media analytics and open source intelligence research trends. This multidisciplinary volume will appeal to students, researchers, and professionals working in the fields of open source intelligence, cyber crime and social network analytics. Chapter Automated Text Analysis for Intelligence Purposes: A Psychological Operations Case Study is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
650 0 _aData protection.
650 0 _aComputational intelligence.
650 0 _aSystem theory.
650 0 _aComputer crimes.
650 0 _aData mining.
650 0 _aMachine learning.
650 1 4 _aData and Information Security.
650 2 4 _aComputational Intelligence.
650 2 4 _aComplex Systems.
650 2 4 _aCybercrime.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aMachine Learning.
700 1 _aTayebi, Mohammad A.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aGlässer, Uwe.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSkillicorn, David B.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030412500
776 0 8 _iPrinted edition:
_z9783030412524
776 0 8 _iPrinted edition:
_z9783030412531
830 0 _aLecture Notes in Social Networks,
_x2190-5436
856 4 0 _uhttps://doi.org/10.1007/978-3-030-41251-7
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c175921
_d175921