Aims and Scopes
Recent decade has witnessed the birth of social media ecosystem that brings social organizations, media content and various stakeholders together, and now it appears significant advantages of comprehensiveness, diversity and wisdom that provide users with higher quality of experiences. With the explosive increase of social users, as well as the popularity of pervasive (mobile) social media tools and services, more and more users are much addicted to share personal feeling, sentiment, idea and experience to a wider range of friends, even friends of friends, by using video, images and photos, etc. Meanwhile, social media ecosystem suffers from security, privacy and trustworthiness threats. How to leverage the power of bottom-top crowd to improve the ecosystem’s efficacy and efficiency, as well as ensure its security and privacy become burning and challenging.

This special issue seeks to publish high-quality original research articles, with a particular emphasis on advanced crowd computing and crowd intelligence methodologies applicable for real-world social media, and encourages more practical and validated techniques, not focused on pure conceptual model, framework and building blocks descriptions.

Topics of interests include below, but are not limited to:
1. Social media network architecture, model and new paradigm by using crowd computing
2. Crowd computing and crowd intelligence methodologies for social media recommendation and sentimental analysis
3. Social media content security, vulnerability and forensics based on crowd intelligence and soft computing
4. Crowd computing-enabling spatial-temporal access control, usage control and digital rights management for both online and offline social media
5. Crowdsourcing-employed security and trustworthiness evaluation and measure of social media services, tools and systems
6. The performance metrics and benchmarks studies on crowd computing for social media
7. Risk management and assessment, as well as social-factor considerations in social media ecosystem by using soft computing
8. Ubiquitous, personal and mobile social media applications based on crowd intelligence
9. Social media prototypes and empirical studies together with crowdsourcing

Instructions for submission
All submitted papers must be clearly written in excellent English and contain only original work and cutting-edges survey, which has not been published by or is currently under review for any other journal or conference. Leading guest editor would prescreen and make an initial determination on the suitability and scope of all submissions, only considering soft computing related and real-world application papers in the topic domain. If suitable, the submission would be assigned to at least three international reviewers; if not, the guest editor would notify authors to resubmit elsewhere.
Papers must be submitted through the Applied Soft Computing website at http://ees.elsevier.com/asoc , where guidelines for the manuscript preparation can also be found (see http://www.journals.elsevier.com/applied-soft-computing/ ). To ensure that all manuscripts are correctly identified for consideration by the Special Issue, the authors should select "Special Issue: Crowd Social Media" when they reach the “Article Type” step in the submission process.
For further information, please contact the leading guest editor at zzy@iastate.edu.

Important dates
Full paper submission deadline: July 31, 2016
First author notification: October 31, 2016 
Revised paper due: December 31, 2016
Final author notification: March 1, 2017 
Expected publication: the second quarter of 2017

Guest editors
Dr. Zhiyong Zhang
Henan Province Distinguished Professor, Henan University of Science & Technology, P. R. of China; Visiting Professor, Department of Computer Science, Iowa State University, USA
E-mail: zzy@iastate.edu, xidianzzy@126.com
Homepage: www.sigdrm.org/~zzhang

Dr. Kim-Kwang Raymond Choo
Fulbright Scholar and Associate Professor, University of South Australia, Australia
E-mail: raymond.choo@fulbrightmail.org

Dr. Arun Kumar Sangaiah
Professor, VIT University, India
E-mail: arunkumarsangaiah@gmail.com

Dr. Liang Chen
University of West London, United Kingdom
E-mail: liang.chen@uwl.ac.uk