Information and Management

Special issue on Social Media Analytics

Guest Editors:

• Weiguo (Patrick) Fan (Virginia Tech, USA), wfan@vt.edu

• Xiangbin Yan (Harbin Institute of Technology, China), xbyan@hit.edu.cn

Call for papers

Online social platforms e.g., Facebook, Twitter, Youtube, Weibo, discussion forums have developed into a virtual world where users and firms share content related to their real lives, works, and various facets of the real world. The explosion of social media usage has resulted in massive user generated contents (UGCs), including  media contents, user information and their interactions on social networks, geo-locations, and many other metadata. These UGCs have created numerous new research opportunities and challenges.

Social media analytics is concerned with developing and evaluating informatics tools and frameworks to collect, monitor, analyze, summarize, and visualize social media data to facilitate conversations and interactions to extract useful patterns and intelligence (Zeng et al. 2010).  Social media analytics generally involve three stage processes: capture, understand, and present (Fan and Gordon, 2014). Recently, more and more research efforts have been dedicated to key issues therein, such as analytics and learning techniques for understanding social media, social media analytics tools and systems, knowledge mining from social media, as well as social network modeling, etc.

This special issue seeks contributions reporting novel solutions, models, theories, or systems regarding social media analytics. Topics of interest include but are not limited to:

• Understanding social content and dynamics

• Understanding firm usage of social media

• Efficient learning algorithms for scalable social media analytics

• Social network modeling using social media data

• Machine learning and data mining for social media

• User interests and behavior modeling in social media

• Tagging, semantic annotation, object and event recognition on large-scale social media collections

• Novel data processing to remove noise and extract useful signals

• Effective search mechanism  in large-scale social media collections

• Novel business applications and value discovery using social media analytics

 

All submissions are required to be done via I&M online submission systems.

Author guidelines are available from http://www.elsevier.com/journals/information-and-management/0378-7206/guide-for-authors. Please indicate in your cover letter that this is a special issue submission on social media analytics.  All submissions will go through an initial screening by guest editors. Only quality submissions will go through the review process.

 

Key Dates:

Online system open for submission:        July 1st to Sept 1st, 2014

First submission paper due:                     Sept 1st, 2014

First round decision made:                       Dec. 1st, 2014

Revised manuscript due:                         March 1st, 2015

Final decision made:                                May 1st, 2015

Final paper due:                                       July 1st, 2015

 

 

Key references:

 

Overview of SMA

• D. Zeng, H. Chen, R. Lusch, & S-H Li, "Social media analytics and intelligence", IEEE Intelligent Systems, 25(6), 2010.

• W. Fan, M. D. Gordon, "Unveiling the power of social media analytics", Communications of ACM, forthcoming, 2014. Preprint available at https://www.researchgate.net/publication/259148570_Unveiling_the_Power_of_Social_Media_Analytics 

• A. S. Abrahams, J. Jiao, W. Fan, G. A. Wang, Z. Zhang, "What is buzzing in the blizzard of buzz: automotive component isolation in social media postings", Decision Support Systems, 55(4), 871-882, 2013.  

• G. A. Wang, J. Jiao, A. S. Abrahams, W. Fan, Z. Zhang, "ExpertRank: A topic-aware expert finding algorithm for online knowledge communities", Decision Support Systems, 54(3), 1442-1451, 2013.  

• A. S. Abrahams, J. Jiao, G. A. Wang, W. Fan, "Vehicle defect discovery from social media", Decision Support Systems, 54(1): 87-97, 2012.  

About Information and Management

 

Information & Management is a premier journal in information systems area. It serves researchers in the information systems field and managers, professionals, administrators and senior executives of organizations which design, implement and manage Information Systems Applications.

 

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• To collect and disseminate information on new and advanced developments in the field of information systems;

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• To encourage further progress in information systems methodology and applications;

• To cover the range of information system development and usage in their use of managerial policies, strategies, and activities for business, public administration, and international organizations.

 

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