  The in-depth analysis of human behavior has been increasingly recognized as a
crucial means for disclosing interior driving forces, causes and impact on
businesses in handling many challenging issues. The modeling and analysis of
behaviors in virtual organizations is an open area. Traditional behavior
modeling mainly relies on qualitative methods from behavioral science and
social science perspectives. The so-called behavior analysis is actually based
on human demographic and business usage data, where behavior-oriented elements
are hidden in routinely collected transactional data. As a result, it is
ineffective or even impossible to deeply scrutinize native behavior intention,
lifecycle and impact on complex problems and business issues. We propose the
approach of Behavior Informatics (BI), in order to support explicit and
quantitative behavior involvement through a conversion from source data to
behavioral data, and further conduct genuine analysis of behavior patterns and
impacts. BI consists of key components including behavior representation,
behavioral data construction, behavior impact analysis, behavior pattern
analysis, behavior simulation, and behavior presentation and behavior use. We
discuss the concepts of behavior and an abstract behavioral model, as well as
the research tasks, process and theoretical underpinnings of BI. Substantial
experiments have shown that BI has the potential to greatly complement the
existing empirical and specific means by finding deeper and more informative
patterns leading to greater in-depth behavior understanding. BI creates new
directions and means to enhance the quantitative, formal and systematic
modeling and analysis of behaviors in both physical and virtual organizations.
