Journal Special Issue on Analyzing and Mining Social Networks for Decision Support

Journal of Universal Computer Science

Journal Special Issue on Analyzing and Mining Social Networks for Decision Support 


Introduction to the Special Issue:

Mining and analyzing social networks is now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amounts of data and by this to discover valuable information from the data. In recent years, due to the booming of social communications and social network-based web services, data mining has become a very important and powerful technique to process and analyze such large amount of data.

Recently, many researchers are focusing on developing new data mining techniques and algorithms, or devoting to improve traditional mining techniques for social network analysis. However, it is meaningless, if the discovered valuable and useful data have not been applied in real application environment. Social data are the aggregations of communication interaction and experience of people, and it if useful to leverage this type of data for decision-making. Thus, it could be an important time to shift the research focus to an application area, such as decision support.

This Journal Special Issue invites papers of the following topics, but never exclusive:

  • Mining and analyzing social data for decision support
  • Mining social web services for decision support
  • Algorithms for mining social networks for decision support
  • Matching engines and interfaces for decision support systems
  • System architectures
  • Intelligent and multi-agent based decision support systems
  • Social decision support systems
  • Semantic Analysis for Decision Support
  • Opinion Mining and Sentiment Analysis
  • Big Data Issue in Mining and analyzing social data for decision support
  • Visualization
  • Experiment and implementation
  • Leveraging social data for decision support in healthcare
  • Case studies and empirical studies


All submissions must be written in English and formatted according to the journal guidelines ( All papers will undergo the special issue guidelines of the journal ( The length of the manuscript prefer not exceed 20 pages. Submissions should be sent to Prof. I-Hsien Ting (

Important Dates:

  • Submission Deadline: October 15, 2015
  • First Notification of Acceptance/Rejection:  December 15, 2015
  • Revised Manuscripts Submission Deadline: January 15, 2016
  • Final Notification of Acceptance/Rejection: February 15, 2016
  • Expected Publication Date: April-May 2016

Guest Editor:

Prof. I-HSIEN TING (Associate Professor in Department of Information Management, National University of Kaohsiung, TAIWAN)

Director of Academic Affairs, Taiwanese Association for Social Networks
Director of Social Network Innovation Research Center, National University of Kaohsiung

Prof. Babiga BIRREGAH (Assistant Professor at Institute Charles Delaunay, University of Technology of Troyes, France)



I-Hsien    Ting    National University of Kaohsiung
Babiga    Birregah    Institut Charles Delaunay, UMR CNRS 6281, University of Technology of Troyes
Georgios    Lappas    Technological Educational Institute (T.E.I.) of Western Macedonia, Kastoria Campus, Greece
Yu-Chieh    Wu    department of cs
Hassan    Naderi Iran University of Science and Technology
Chutisant    Kerdvibulvech    
Rung-Ching    Chen    Chaoyang University of Technology
Patricia    Santos    
Yun    Liu    
Koquilamballe    K    Easwari Engineering College
G. S    Mahalakshmi    
Amalia    Triantafillidou    
Olga    Vasileiadou    
Mariluz    Guenaga    Deusto Institute of Technology - University of Deusto
Pablo    Garaizar    Universidad de Deusto
Lorena    Fernández    
Vanja    Smailovic    Ericsson
Vedran    Podobnik    University of Zagreb
Jaroslaw    Jankowski    West Pomeranian University of Technology
Kostas    Kolomvatsos    Postoctoral Researcher
Sebastian    Dennerlein    
Elisabeth    Lex    Know-Center GmbH