Social Network Analysis and Mining (SNAM) is a multidisciplinary journal serving researchers and practitioners in academia and industry. It is the main venue for a wide range of researchers and readers from computer science, network science, social sciences, mathematical sciences, medical and biological sciences, financial, management and political sciences. We solicit experimental and theoretical work on social network analysis and mining using a wide range of techniques from social sciences, mathematics, statistics, physics, network science and computer science.

92% of authors who answered a survey reported that they would definitely publish or probably publish in the journal again

Journal information

Editor-in-Chief
  • Reda Alhajj
Publishing model
Hybrid (Transformative Journal). Learn about publishing Open Access with us

Journal metrics

99 days
Submission to first decision
222 days
Submission to acceptance
117,961 (2020)
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This journal has 39 open access articles

Journal updates

  • Special Issue on Complex Networks & Applications

    This special issue presents a wide range of complex networks theoretical works and applications focused on social environments such as Information Spreading in Social Media, Rumor and Viral Marketing, Quantifying Success through Social Network Analysis, Human behavior & mobility, Social Reputation, Influence, and Trust.

    New Content Item
  • Big Data Analytics and Deep Learning for Social Network Security

    Network analysis may play a considerable role in the new setup. However, security becomes a major issue when it comes to big data and network analysis in a distributed environment. Therefore, big data analysts, network security experts, and data scientists hold a prominent position in the current era, where data scientists are highly needed and there is a visible shortage in the market. This special issue highlights the challenges and solutions of Deep Learning and Network Security algorithms for Big Data, to improve the effectiveness for data security.

    New Content Item
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About this journal

Electronic ISSN
1869-5469
Print ISSN
1869-5450
Abstracted and indexed in
  1. ACM Digital Library
  2. CNKI
  3. DBLP
  4. Dimensions
  5. EBSCO Discovery Service
  6. EI Compendex
  7. Emerging Sources Citation Index
  8. Google Scholar
  9. INSPEC
  10. Institute of Scientific and Technical Information of China
  11. Japanese Science and Technology Agency (JST)
  12. Naver
  13. OCLC WorldCat Discovery Service
  14. ProQuest Advanced Technologies & Aerospace Database
  15. ProQuest Central
  16. ProQuest SciTech Premium Collection
  17. ProQuest Technology Collection
  18. ProQuest-ExLibris Primo
  19. ProQuest-ExLibris Summon
  20. SCImago
  21. SCOPUS
  22. TD Net Discovery Service
  23. UGC-CARE List (India)
  24. WTI Frankfurt eG
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