Today, computer-mediated communication (CMC) and social computing systems, ranging from instant messaging to twitter, have become a pervasive tool that people use to accomplish their collaboration needs. One argument is that CMC tools are not passive channels that are neutral to communication itself. Instead, CMC systems can be smart computing artifacts. CMC may listen to communication content, and actively involve in communication activities to shape social processes and outcomes. There is a broad space to apply computational techniques to endow CMC with functional properties beyond only passive mediation for supporting group activities. The social impact of identifying useful designs can be enormous.
In my research, I examine the active and participatory aspect of CMC with insights from AI and behavioral and social sciences. I use machine learning and text processing techniques to augment communication channels with new task-oriented functions. By looking at the cases of using automated feedback for supporting intercultural teamwork and collaborative learning, I will illustrate how full-fledged behavioral experimentation and computation-driven analyses can help to better design, evaluate and understand the properties of interactive systems. I will present the potentially fruitful space for future research in the technical aspect (language technologies, AI, multimedia etc.) and pragmatic aspect (persuasive and affective computing etc.) of social and interactive computing.
Hao-Chuan Wang is a Ph.D. candidate in the Department of Information Science at Cornell University. Between 2006 and 2008, he was a Ph.D. student at the School of Computer Science, Carnegie Mellon University, where he conducted research at the Human-Computer Interaction Institute and the Language Technologies Institute. Between 2004 and 2006, he was a research assistant at the Institute of Information Science, Academia Sinica. He received his M.S. in Computer Science from National Chengchi University in 2004 and his B.S. from National Taiwan Normal University in 1999. Mr. Wang’s primary research interests lie in the areas of human-computer interaction, social computing, artificial intelligence and educational technologies. His recent projects include designing and evaluating systems for group creativity, investigating the effects of culture on online communication, and supporting collaborative learning with language processing and conversational agent. More information can
be found at his website: