Workshop in it: collaborative innovation networks

Lectures: 2 sessions / week, 2 hours / session

The emergence of online social networks opens up unprecedented opportunities to read the collective mind, discovering emergent trends while they are still being hatched by small groups of creative individuals. The Web has become a mirror of the real world, allowing researchers in predictive analytics to study and better understand why some new ideas change our lives, while others never make it from the drawing board of the innovator.

Diversity begets creativity—in this seminar we tap the amazing power of swarm creativity on the Web by studying and working together as Collaborative Innovation Networks (COINs). As interdisciplinary teams of MIT management, Savannah College of Art and Design, University of Cologne informatics, and Aalto University software engineering students we will explore how to discover latest trends on the Web, and how to make them succeed in online social networks.

We study a wide range of methods for predictive analytics (coolhunting) and online social marketing (coolfarming), mostly based on social network analysis and the emerging science of collaboration. Our methods are based on analysis of large corpora of digital traces of human activity, in particular the Web, Blogs, online forums, social networking sites, e-mail archives, phone logs, and face-to-face interaction through using sociometric badges. Students will also learn to use our own unique MIT-developed Condor tool for Web mining, social network analysis, and trend prediction.

Students will be asked to do preparatory readings. During class, small teams will be asked to present an overview of research topics based on the papers listed below. In the second half of the seminar, small student teams with participants from MIT, SCAD, Aalto University (Helsinki), and University of Cologne (Germany) will work on their own trend analysis, prediction, and viral marketing projects using Web mining and dynamic SNA tools and methods, gaining invaluable insights about global virtual collaboration and about themselves as members of cross-disciplinary global virtual teams.

Because this course relies heavily on class participation for its success, class norms and expectations regarding class behavior are very important:

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