Social Networking Big Data Opportunities, Solutions, and Challenges

  in Special Issue   Posted on July 19, 2016

Information for the Special Issue

Submission Deadline: Thu 15 Dec 2016
Journal Impact Factor : 3.997
Journal Name : Future Generation Computer Systems
Journal Publisher:
Website for the Special Issue: http://www.journals.elsevier.com/future-generation-computer-systems/call-for-papers/special-issue-on-social-networking-big-data-opportunities-so
Journal & Submission Website: https://www.journals.elsevier.com/future-generation-computer-systems

Special Issue Call for Papers:

Social Networking Big Data is a collection of very huge data sets with a great diversity of types from social networks. The emerging paradigm of social networking and big data provides enormous novel approaches for efficiently adopting advanced networking communications and big data analytic schemas by using the existing mechanism. The rapid development of Social Networking Big Data brings revolutionary changes to our daily lives and global business, which has been addressed by recent research. However, as attackers are taking advantages of social networks to achieve their malicious goals, the security issue is also a critical concern when using Social Networking Big Data in practice.

Due to the complexity and diversity of the Social Networking Big Data, there are two important aspects of Social Networking Big Data. One is how to conduct social network analysis based on Big Data, the other is how to using Big Data analytic technique to ensure security of social networks using various security mechanism. Current work on Social Networking Big Data focuses on information processing, such as data mining and analysis. However, security, trust and privacy of Social Networking Big Data are remarkably significant for current researchers and practitioners to address these issues, and seek out the efficient methods to different threats. This special issue will concentrates on the challenging topic – “Social Networking Big Data”, and aims to solicit both original research and tutorial papers that discuss the security, trust and privacy of Social Networking Big Data.

About the Topics of Interest

Any topic related to Social Networking Big Data aspects, including social networks, social influence analysis, big data, security, trust and privacy, will be considered.
All aspects of design, theory and realization are of interest. The scope and interests for the special issue include but are not limited to the following list:

(i) Fundamentals and Technologies for Social Networking Big Data

Modeling on social influence with big data
Social influence analysis with big data
Influence propagation in large‐scale social networks
Dynamic social influence in large‐scale social networks
Influence maximization problem with big data
User behavior analysis with social influence evaluation
Social influence analysis in heterogeneous social network
Casual relationship in large‐scale social networks
Methods for distinguishing the positive, negative, and controversy influence
Models, methods, and tools for influence propagation
Community detection methods with big data
Modeling community influence in social networks
Impact of social networks on human social behavior
Human behavior analysis in social networks with big data
Impact of social networks on human social behavior
Recommendations and advertising in social networks with big data
Modeling on the characteristics and mechanisms of social networks

(ii) Security, Trust and Privacy for Social Networking Big Data

Modeling on malicious information propagation with social influence analysis
Secure social networking application with social influence analysis
Privacy in management and analysis of social networking big data
Prevention of malware propagation in social networks
Modeling on the secure mechanisms of social networks
Novel secure solutions for designing, supporting and operating social networks
Trust evaluation in social networks with big data
Threat and vulnerability analysis in social networks
Secure social network architecture with big data
Privacy protection in social networks with big data
Secure social networking applications with big data
Security design for social networks in big data
Models, methods, and tools for testing the security of social networks
Trust management in social networks with big data
Spam problems in social networks with big data
Detection for malicious information propagation in social networks

Submission Format and Guideline

All submitted papers must be clearly written in excellent English and contain only original work, which has not been published by or is currently under review for any other journal or conference. Papers must not exceed 25 pages (one‐column, at least 11pt fonts) including figures, tables, and references. A detailed submission guideline is available as “Guide to Authors” at: https://www.elsevier.com/journals/future-generation-computer-systems/0167-739X/guide-for-authors

All manuscripts and any supplementary material should be submitted through Elsevier Editorial System (EES). The authors must select “SI: SNBD-OSC” when they reach the “Article Type” step in the submission process. The EES website is located at: http://ees.elsevier.com/fgcs

All papers will be peer-reviewed by at least three independent reviewers. Requests for additional information should be addressed to the guest editors.

Important dates (Tentative)

Submission deadline: December 15, 2016

First-roundpass notification: (for a rejected paper) December 30, 2016

Review result notification: April 1, 2017

Acceptance/rejection notification: June 1, 2017

Publication: December, 2017

Guest Editors:

Sancheng Peng (corresponding guest editor)

Shui Yu

Peter Mueller

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