The Emergence of Social and Community Intelligence

Daqing Zhang, Bin Guo, Zhiwen Yu
2011 Computer  
COMPUTER 22 PERSPECTIVE S EVOLUTION OF SOCIAL AND COMMUNITY INTELLIGENCE RESEARCH T he understanding of human behavior, social interactions, and city dynamics has long relied on data collected through individual observations and surveys. Unfortunately, observations were usually sparse, and survey results were often incomplete and significantly delayed. With advances in computing, storage, Internet access, wireless communication, and sensing, it is now possible to monitor and analyze human
more » ... or, social interactions, and city dynamics on a large scale and in nearly real time. Initially, analysts used Internet content as the premier data source for understanding large-scale human interaction. Then the emergence of static sensing infrastructure made it possible to recognize human activities in a physical environment. Recently, the prevalence of sensor-enriched mobile devices has brought unprecedented opportunities to observe human behavior, social interaction, and community dynamics. The Internet and Web, static infrastructure, and wearable and mobile devices have all contributed to the evolution of SCI research. Internet services and Web applications The past two decades have witnessed the explosive growth of Internet services, such as e-mail, instant messaging, and Web applications, which have changed how people share and obtain information and communicate with each other. A large body of work has centered on leveraging those services, including efforts in information extraction and human interaction analysis, such as news recommendation, personal and organizational profile extraction, and e-mail network analysis. As the Internet moves into the Web 2.0 era, researchers are turning their attention to online social utilities, such as social networking sites, wikis, and blogs. Much work has focused on social behavior study and usergenerated content analysis. A group from the University of Koblenz-Landau has investigated how to mine social networks to study customer behavior. 1 Researchers from Purdue University have developed an unsupervised model to estimate relationship strength from interaction activity and user similarity on a social website. 2 Investigators from Wright State University label Web 2.0 service users as "citizen sensors" and have worked on social event detection from user-contributed contents. 3 Collaborators from the University of Arizona, Carnegie Mellon University, and the University of Southern California coined the term "social computing," defining it as social study based on the Internet and Web that aims to study and extract human social dynamics from online human interactions. 4
doi:10.1109/mc.2011.65 fatcat:ati2z2ncnng45hxobax4t7vsga