Special Issue on Online Behavioral Analysis and Modeling

Submission Deadline: 1 June 2015
Publication: January/February 2016

With the rapid proliferation of web applications, such as search engines, e-commerce platforms, and social networking services, more of users’ online behaviors are available, opening a new perspective for behavioral data analytics where more focus can be put to the various types of interactions on the web. For example, users can build friendships with, send messages to, and make phone calls with other users, creating user-user interactions; they can also post messages, buy products, and check in at restaurants, creating user-item interactions. Developing computational methods to model user behaviors, analyze different behavioral patterns, understand mechanisms underlying behavioral logs, and eventually predict the next behaviors or detect strange behaviors is of paramount importance, as it would improve applications like web search, recommender systems, and social networking services. Additionally, it could help counter fraud, spam, and attacks. This presents clear challenges to online behavior modeling since user behavior depends on content, intentions, and contexts in complex online environments. Moreover, the online setting brings big challenges to behavioral data analysis since user behavioral data is in web scale, heterogeneous, of multiple dimensions, highly sparse, and dynamic.

The topics of interest for this special issue include, but are not limited to:

  • Methods and techniques of online user behavioral analytics:
    • New principles of user behavior formation
    • Modeling personal preference and interpersonal influence
    • Modeling individual behavior and group behavior
    • Modeling temporal behavior and behavioral dynamics
    • Modeling check-in behavior and purchasing behavior
    • Scalable techniques for large-scale behavioral data analysis
    • Efficient techniques for online behavioral processing
  • Applications of online user behavioral analytics, such as:
    • Social networks
    • Recommender systems
    • E-commerce systems
    • Fraud and spam detection
    • Suspicious behavior detection
    • Search engines

Guest Editors

  • Peng Cui, Tsinghua University, China
  • Huan Liu, Arizona State University, US
  • Charu Aggarwal, IBM T. J. Watson Research Center, US
  • Fei Wang, University of Connecticut, US

Submission Guidelines

Submissions should be 3,000 to 5,400 words (counting a standard figure or table as 200 words) and should follow IEEE Intelligent Systems style and presentation guidelines (www.computer.org/intelligent/author). The manuscripts cannot have been published or be currently submitted for publication elsewhere.

We strongly encourage submissions that include audio, video, and community content, which will be featured on the IEEE Computer Society Website along with the accepted papers.


Information about the special issue's focus: Peng Cui, is1-2016@computer.org
General author guidelines: www.computer.org/intelligent/author
Submission details: contact intelligent@computer.org
To submit an article: https://mc.manuscriptcentral.com/is-cs