Call For Papers: Special issue of the Neurocomputing

In recent years, social network research has advanced significantly, thanks to the prevalence of the online social websites and instant messaging systems as well as the availability of a variety of large-scale offline social network systems. These social network systems are usually characterized by the complex network structures and rich accompanying contextual information. Nowadays they are key platforms for, among others, content dissemination, professional networking, recommendation, scouting, alerting, and political campaigns. Researchers are increasingly interested in addressing a wide range of challenges residing in the multi-source of large-scale data about the human behavior in social networks. It spans a number of disciplines, across numerous fields in and beyond computer science, all the way up to the analysis of social relationships and how they evolve and mature over time. These issues have important implications on community discovery, anomaly detection, and tre!
nd prediction, and they can enhance applications in multiple domains such as information retrieval, recommendation systems, trust and security and so on. Research in behavior analysis is a fertile ground also for industry, to develop innovative ideas fostering the design of the new generation of social network platforms and their services.

This special issue seeks contributions pushing the state of the art in all facets of behavior analysis in social networks highlighted above. We also encourage original work based on an interdisciplinary research (at the boundary between computer science and humanistic disciplines such as sociology and anthropology) where quantitative evidence is available demonstrating the mutual advantage of such an approach. Moreover, special attention is expected in interpreting the proposed research results in order to shed light towards what users may need and wish in terms of novel, practical services and applications.

Topics of particular interest (but not limited to):
Design of social network platforms based on human behavioral models
Analysis of users' behavior and its evolution over time
Impact of Online Social Networks on human social behavior
Collective behavior analysis in social networks
Prevention of misbehaviors (spamming, phishing, ...) in social networks
Sentiment analysis for behavior analysis in social networks
Data Mining and Machine Learning to gain novel insights on behavior analysis in social networks
Deep learning for behavior analysis in social networks
Data mining on dynamic, heterogeneous and large-scale behavior analysis
Real-world applications of behavior analysis in social networks

Timeline
Submission deadline: April 15th, 2015
First round decision: July 1st, 2015
Expected Publication: Spring 2016

Authors should prepare their manuscript according to the Instructions for Authors available from the online submission page of the Neurocomputing Journal at elsevier.com. All the papers will be peer-reviewed following the Neurocomputing reviewing procedures.

Notes: when submitting your manuscript, at the step of ¡°Select Article Type¡±, please choose this special issue: 'SI:Behavior Analysis in SN' as the 'Article Type'.

Guest Editors:
Prof. Meng Wang, Hefei University of Technology (eric.mengwang@gmail.com)
Prof. Ee-Peng Lim, Singapore Management University (eplim@smu.edu.sg)
A/Prof. Lei Li, Hefei University of Technology (lilei@hfut.edu.cn)
Prof. Mehmet Orgun, Macquarie University (mehmet.orgun@mq.edu.au)