Calls for Papers (special): International Journal of Virtual Communities and Social Networking (IJVCSN)


Special Issue On: Information Processing from Social Networking Big Data

Submission Due Date
8/1/2017

Guest Editors
Fuqian Shi, PhD
Wenzhou Medical University, Wenzhou, P.R. China
shifuqian@gmail.com

Samarjeet Borah, PhD
Department of Computer Applications, Sikkim Manipal Institute of Technology, Majitar, Sikkim
samarjeetborah@gmail.com

Chintan Bhatt, PhDc
U & P U Patel Department of Computer Engineering, Charotar University of Science and Technology (CHARUSAT), Changa, Gujarat, India
chintanbhatt.ce@charusat.ac.in

Amira S. Ashour, PhD
Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Egypt
amirasashour@yahoo.com

Nilanjan Dey, PhD
Department of Information Technology, Techno India College of Technology, India
neelanjan.dey@gmail.com

Vishal Bhatanagar
Department Computer-Science and Engineering at Ambedkar Institute of Advanced Communication Technologies and Research, Delhi, India
vishalbhatnagar@yahoo.com

Introduction

Nowadays, social media and networks generates massive amount of information, which requires new technologies and techniques, including the emerging domain of big data. Social networks provide fast and free communication and information sharing between individuals using Facebook, tweets, videos, pictures, and texts. The individuals’ behavior and opinion through the social networks influence while interacting with others, which lead to several interesting collective phenomena. Numerous efforts have been devoted to explore the social networks’ robustness in the presence of malicious threats and the collective behavior in the framework of various network topologies. Furthermore, social networks activities generate a huge amount of data which is big in size and complex in structure. In addition, big data has become vital as many public and private organizations have been collecting gigantic amounts of domain-specific information. Thus, social networks data processing requires accurate computational algorithms, information processing and efficient mathematical models. Since social networks are sources of diverse and massive big data, thus theoretical data processing techniques and novel applications investigation become a must to help solve big data processing challenges.

In addition, social networks increase the number of users leading to security problem and loss of privacy due to the possibility to trace relations, activities, and communication between. Consequently, information management by different kinds of social networks is very significant for its impact on the overall personal profile. Social networks data analysis of some public, encrypted data sets can be applied to solve the security issues. Social network data analysis based on big data using analytic techniques to ensure social networks security through various security mechanisms attracts several researchers. Thus, social networking big data requires information processing including data mining/analysis, text analytics, and semantic analysis.

This special issue focuses on addressing distributed information processing concepts, techniques and challenges in social networks. It discusses security, privacy and trust of social networking big data. The special issue provides useful foundation for several types of social media analytics to monitor social networking sites, and to measure the effectiveness of an organization's social media strategies that influence customer sentiment. The special issue reports big data analysis techniques associated with the business impact of social networks. Developing efficient methods to different threats is remarkably significant for researchers, thus this special issue addresses several challenging topic for the social networking big data. It invites submissions from all related disciplines to introduce comprehensive and diverse perspectives. The main goal of this special issue is to achieve outstanding research and improvements in the social networking big data and their applications in wide range of applications.



Objective

This call for papers is for a special issue of the IJVCSN dedicated to high quality papers in the social networking applications. Our objective is to publish the latest new trends and advancements in the related topics. Establishing a scientific forum to introduce the researchers’ thoughts and developments for information processing based social networking big data techniques and their applications in several domains is our main concern.



Recommended Topics

Topics to be discussed in this special issue include (but are not limited to) the following:

  • Social media computing and networking
  • Dynamic social networks
  • Modeling and strategic of social networks
  • Social learning, and decision-making
  • Multi-layered social networks
  • Big data analytics and management
  • Big data analytics: data streaming, high-dimensional data, models scalability, and distributed computing.
  • Big data search and mining in social networking
  • Social networking big data processing
  • Big data security, privacy and trust
  • Cloud big data analytics
  • Systems and Algorithms for big data Search
  • Big data analytics and deep learning in social networking
  • Machine learning, data mining, information processing and statistical inference frameworks for handling big data from social networks
  • Data-driven applications
  • Graphical modeling, trust, privacy, and engineering applications in social networks
  • Web Search
  • Social networking challenges and limitations


Submission Procedure

Researchers and practitioners are invited to submit papers for this special theme issue on Information Processing from Social Networking Big Data on or before August 1, 2017. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at: http://www.igi-global.com/development/author_info/guidelines submission.pdf. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.



All submissions and inquiries should be directed to the attention of:
Nilanjan Dey, PhD
Lead Guest Editor
International Journal of Virtual Communities and Social Networking (IJVCSN)
Email: neelanjan.dey@gmail.com