Identification of Pathogenic Social Media Accounts (Record no. 177968)

MARC details
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001 - CONTROL NUMBER
control field 978-3-030-61431-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125435.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030614317
-- 978-3-030-61431-7
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-030-61431-7
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q334-342
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA347.A78
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Alvari, Hamidreza.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Identification of Pathogenic Social Media Accounts
Medium [electronic resource] :
Remainder of title From Data to Intelligence to Prediction /
Statement of responsibility, etc by Hamidreza Alvari, Elham Shaabani, Paulo Shakarian.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2021.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2021.
300 ## - PHYSICAL DESCRIPTION
Extent IX, 95 p. 25 illus., 19 illus. in color.
Other physical details online resource.
336 ## -
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-- computer
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-- online resource
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490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Computer Science,
International Standard Serial Number 2191-5776
520 ## - SUMMARY, ETC.
Summary, etc This book sheds light on the challenges facing social media in combating malicious accounts, and aims to introduce current practices to address the challenges. It further provides an in-depth investigation regarding characteristics of “Pathogenic Social Media (PSM),”by focusing on how they differ from other social bots (e.g., trolls, sybils and cyborgs) and normal users as well as how PSMs communicate to achieve their malicious goals. This book leverages sophisticated data mining and machine learning techniques for early identification of PSMs, using the relevant information produced by these bad actors. It also presents proactive intelligence with a multidisciplinary approach that combines machine learning, data mining, causality analysis and social network analysis, providing defenders with the ability to detect these actors that are more likely to form malicious campaigns and spread harmful disinformation. Over the past years, social media has played a major role in massive dissemination of misinformation online. Political events and public opinion on the Web have been allegedly manipulated by several forms of accounts including “Pathogenic Social Media (PSM)” accounts (e.g., ISIS supporters and fake news writers). PSMs are key users in spreading misinformation on social media - in viral proportions. Early identification of PSMs is thus of utmost importance for social media authorities in an effort toward stopping their propaganda. The burden falls to automatic approaches that can identify these accounts shortly after they began their harmful activities. Researchers and advanced-level students studying and working in cybersecurity, data mining, machine learning, social network analysis and sociology will find this book useful. Practitioners of proactive cyber threat intelligence and social media authorities will also find this book interesting and insightful, as it presents an important andemerging type of threat intelligence facing social media and the general public.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer networks
General subdivision Security measures.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mobile and Network Security.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Shaabani, Elham.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Shakarian, Paulo.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030614300
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030614324
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title SpringerBriefs in Computer Science,
-- 2191-5776
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-030-61431-7">https://doi.org/10.1007/978-3-030-61431-7</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

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