Introduction

What is Behavior Informatics?

Behavior Informatics (BI) aims to develop methodologies, techniques and practical tools for representing, modeling, analyzing, mining, understanding and utilizing of behaviors (events, actions, activities and their sequences), behavior interactions and networks, behavioral patterns, behavioral impacts, behavior dynamics, the formation of behavior-oriented groups and collective intelligence, and behavioral intelligence emergence etc of human beings, organisms, systems, organizations and artificial entities in conjunction with their environments. Such techniques contribute to the discovery of behavior intelligence.In more detail,behavior informatics addresses the following key aspects.

  • Behavioral data: In preparing behavioral data, behavioral elements hidden or dispersed in transactional data need to be extracted and connected, and further converted and mapped into a behavior-oriented feature space, or behavioral feature space. In the behavioral feature space,behavioral elements are presented in behavioral item sets.Figure 1 illustrates the mapping and conversion from transactional data to behavioral data.
  • Behavioral representation and modeling: The goal is to develop behavior-oriented specifications for describing behavioral elements and the relationships amongst the elements. The specifications reshape the behavioral elements to suit the presentation and construction of behavioral sequences. Behavioral modeling also provides a unified mechanism for describing and presenting behavioral elements, behavioral impact and patterns.
  • Behavioral impact analysis: For analyzing behavioral data, we are particularly interested in those behavioral instances that are associated with having a high impact on business processes and/or outcomes. Behavioral impact analysis features the modeling of behavioral impact.
  • Behavioral pattern analysis: There are in general two ways of conducting behavioral pattern analysis. One is to discover behavioral patterns without the consideration of behavioral impact; the other is to analyze the relation-ships between behavior sequences and particular types of impact.
  • Behavioral intelligence emergence: To understand behavioral impact and patterns, it is important to scrutinize behavioral occurrences, evolution and life cycles, as well as the impact of particular behavioral rules and patterns on behavioral evolution and intelligence emergence (for instance, the emergence of swarm intelligence from a group of interactive agents). An important task in behavioral modeling is to define and model behavioral rules, protocols and relationships, and their impact on behavioral evolution and intelligence emergence.

 

 

 

What is Social Informatics?

 

Social informatics is a general term for an area of informatics that is concerned with the intersection of social behavior and computational systems. It has become an important concept for use in business. It is used in two ways as detailed below.

In the weaker sense of the term, social informatics has to do with supporting any sort of social behavior in or through computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology. Thus, blogs, email, instant messaging, social network services, wikis, social bookmarking and other instances of what is often called social software illustrate ideas from social computing, but also other kinds of software applications where people interact socially.

In the stronger sense of the term, social informatics has to do with supporting “computations” that are carried out by groups of people. Examples of social informatics in this sense include collaborative filtering, online auctions, prediction markets, reputation systems, computational social choice, tagging, and verification games.

Overall, social informatics can be defined as follows:

“Social Informatics” refers to processes that support the gathering, representation, processing, use, and dissemination of information that is distributed across social collectivities such as teams, communities, organizations, and markets. Moreover, the information is not “anonymous” but is significant precisely because it is linked to people, who are in turn linked to other people.

Why do we need Behavior and Social Informatics and Computing?

Behavior and Social Informatics is a multidisciplinary research issue, which may involve knowledge in areas such as behavioral science, user modeling, knowledge representation, ontological engineering, semantic web, data mining and knowledge discovery, artificial intelligence, machine learning, system simulation, artificial social system, open complex systems, swarm intelligence, impact analysis, risk analysis, social network analysis, group formation, organizational behavior analysis, cause-effect analysis, reasoning and learning. Domain knowledge is crucial for behavior understanding and analysis in that specific area.

 

 

What are the benefits of developing Behavior and Social Informatics and Computing?

 

 

With the development of foundations and technical tools for BI, it is helpful for us to have in-depth understanding, modeling, representation, analysis and utilization of behaviors, group behaviors, and social behavior networks toward cause-effect-oriented problem understanding and solving. This includes but is not limited to behavior understanding, exceptional behavior analysis, opportunities use, behavior pattern analysis, behavior impact analysis, and cause-effect analysis.

Deep and quantitative behavior analysis such as in social network cannot be supported by methodologies and techniques in traditional behavioral sciences due to the behavior implication in normal transactional data. In addition, various social computing applications such as blogs, email, instant messaging, social networking (Facebook, Twitter, LinkedIn, etc.), wikis, and social bookmarking have been widely popularized where people interact socially via computing space. Such applications have been profoundly impacting social behavior and life style of human beings while pushing the boundary of computing technology simultaneously. The synthesis of behavior and social informatics creates a practical bridge linking and promoting the researches and applications between information technology and behavior and social science. Therefore, it is imperative to develop new behavioral and social analytics technologies that can derive an accurate understanding of human behaviors and social characteristics beyond the traditional demographic and historical tracking. This leads to the emergence of the inter-disciplinary Behavior Informatics and Social Computing.

 

 

What knowledge may be needed for Behavior and Social Informatics and Computing?

 

 

In understanding and solving many issues and problems, Behavior emerges as a key driving force, in both artificial and human societies. Behavior is connected to many entities and objects, such as behavior subjects, objects, causes, impacts, scenarios and constraints and environments. In addition, many relevant behaviors consist of social behavior networks, which involve social, organizational and collective factors and intelligence. To effectively understand such behaviors and their dynamics and influence, it is important to build formal methods and workable tools for behavior representation, processing and engineering, namely behavior informatics.

Social informatics begins with the observation that humans and human behavior are profoundly social. From birth humans orient to one another, and as they grow they develop abilities for interacting with one another ranging from expression and gesture to spoken and written language. As a consequence, people are remarkably sensitive to the behavior of those around them, and make countless decisions that are shaped by their social context. Whether it's wrapping up a talk when the audience starts fidgeting, choosing the crowded restaurant over the nearly deserted one, or crossing the street against the light because everyone else is doing so, social information provides a basis for inferences, planning, and coordinating activity.

The premise of social informatics is that it is possible to design digital systems that support useful functionality by making socially produced information available to their users. This information may be provided directly, as when systems show the number of users who have rated a review as helpful or not. Or the information may be provided after being filtered and aggregated, as is done when systems recommend a product based on what else people with similar purchase history have purchased. Or the information may be provided indirectly; as is the case with Google's page rank algorithms which orders search results based on the number of pages that (recursively) point to them. In all of these cases, information that is produced by a group of people is used to provide or enhance the functioning of a system. Social informatics is concerned with systems of this sort and the mechanisms and principles that underlie them.

Recent year witnessed the emergence and prevalence of social Web, in the forms of social networking, microblogging, social annotation, forums and Wikis. During the interactions between users and systems, a massive volume of data in various forms (i.e., big data) has been archived and therefore user behavioral and social features have stamped into this big data. All these create an urgent and valuable challenge for researchers from either technological or social science backgrounds to work together to better understand the hidden knowledge within it and significant facilitate the existing services and systems. The synergy of behavior informatics and social informatics is a timely response to this practice call.

What are the benefits of developing Behavior and Social Informatics and Computing?

 

With the development of foundations and technical tools for BI, it is helpful for us to have in-depth understanding, modeling, representation, analysis and utilization of behaviors, group behaviors, and social behavior networks toward cause-effect-oriented problem understanding and solving. This includes but is not limited to behavior understanding, exceptional behavior analysis, opportunities use, behavior pattern analysis, behavior impact analysis, and cause-effect analysis.

Deep and quantitative behavior analysis such as in social network cannot be supported by methodologies and techniques in traditional behavioral sciences due to the behavior implication in normal transactional data. In addition, various social computing applications such as blogs, email, instant messaging, social networking (Facebook, Twitter, LinkedIn, etc.), wikis, and social bookmarking have been widely popularized where people interact socially via computing space. Such applications have been profoundly impacting social behavior and life style of human beings while pushing the boundary of computing technology simultaneously. The synthesis of behavior and social informatics creates a practical bridge linking and promoting the researches and applications between information technology and behavior and social science. Therefore, it is imperative to develop new behavioral and social analytics technologies that can derive an accurate understanding of human behaviors and social characteristics beyond the traditional demographic and historical tracking. This leads to the emergence of the inter-disciplinary Behavior Informatics and Social Computing.