저널 정보

Social Network Analysis and Mining

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영향력 지수:
2.8
출판사:
Springer
ISSN:
1869-5450
조회:
23585
팔로우:
7
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논문 모집

Social Network Analysis and Mining is an academic journal published by Springer. (ISSN 1869-5450, impact factor 2.8).

Aims and scope 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. The main areas covered by SNAM include: (1) data mining advances on the discovery and analysis of communities, personalization for solitary activities (e.g. search) and social activities (e.g. discovery of potential friends), the analysis of user behavior in open forums (e.g. conventional sites, blogs and forums) and in commercial platforms (e.g. e-auctions), and the associated security and privacy-preservation challenges; (2) social network modeling, construction of scalable and customizable social network infrastructure, identification and discovery of complex, dynamics, growth, and evolution patterns using machine learning and data mining approaches or multi-agent based simulation; (3) social network analysis and mining for open source intelligence and homeland security. Papers should elaborate on data mining and machine learning or related methods, issues associated to data preparation and pattern interpretation, both for conventional data (usage logs, query logs, document collections) and for multimedia data (pictures and their annotations, multi-channel usage data). Topics include but are not limited to: Applications of social network in business engineering, scientific and medical domains, homeland security, terrorism and criminology, fraud detection, public sector, politics, and case studies Anomaly and outlier detection in social networks Behavior and identity detection and monitoring Community discovery in large-scale and complex social networks Contextual social network analysis Data models and query models for social networks and social media Data preparation for social network analysis and mining Data protection inside communities Dynamics and evolution patterns of social networks, trend prediction Evolution of communities in the Web Information acquisition and establishment of social relations Large-scale graph algorithms Link and node prediction in social networks Misbehaviour detection in communities Mobile and stream data analysis for social network applications Multi-agent based social network modeling and analysis Multidisciplinary applications of social network analysis Network integration and conflict resolution Online social networking and human computer interaction Pattern presentation for end-users and experts Personalization for search and for social interaction Recommendations for e-commerce and business applications Recommendation networks Search algorithms on social networks Security and privacy in social networks Social media monitoring and analysis Spatio-temporal aspects in social networks and social media Tools and infrastructures for social networking platforms Web 2.0 and Web communities
최종 수정: Dou Sun ()

관련 저널

CCF정식 명칭영향력 지수출판사ISSN
Computational Social NetworksSpringer2197-4314
Journal of Computational Analysis and ApplicationsSpringer1521-1398
Cybernetics and Systems Analysis0.7Springer1060-0396
Journal of Network and Systems Management3.9Springer1064-7570
Statistical Analysis and Data MiningWiley1932-1872
BioData Mining6.1Springer1756-0381
International Journal of Document Analysis and Recognition2.5Springer1433-2833
Computing2.8Springer0010-485X
Advances in Data Analysis and Classification1.3Springer1862-5347
Network SecurityElsevier1353-4858

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