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 42 open access articles

Journal updates

  • Special Issue on Deviant Behaviors on Social Media

    Deviance on social media is concerned with the use of social media by deviant or malicious actors to cause unusual, unaccepted, illegal or harmful acts that affect individuals or society in general. The primary goal of this special issue is to exchange the latest fundamental advances in the state of the art and practice of studying deviance on social media. We are interested in studies not only with strong algorithmic innovations but also with solid application-oriented experimental evaluations and system implementations.

    New Content Item
  • Call for Papers: Pervasive Health: Social Media Analytics and Sensing for Healthcare and well-being

    Artificial intelligence (AI) is changing the landscape of healthcare and modern personalized precision medicine. With the increasing availability of healthcare data and rapid progress of machine learning algorithms, AI and big data analytics are enabling unprecedented analysis of healthcare. Social media networks, when combined with Big Data applications and health policymaking, enable the development of smart public health applications that will result in high-quality health delivery and reduced costs.

    New Content Item
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About this journal

Electronic ISSN
1869-5469
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