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New ISOM Elective Available for Spring 2015

MIS491 002 Social Media Analytics – Monday from 7:20PM-10:00PM (CRN 21949) – Open for registration in Patriot Web.

Course Description
The explosive growth and adoption of social media such as Facebook, Twitter, YouTube, Instagram has transformed the way we express our preferences, communicate with others, and share information. This course will cover the history, theory, technologies, practical uses of social media, and topics in social data analysis. Students will have hands-on experience of using social media data for answering a particular question, analyzing the data for strategies, and measuring their effectiveness. By completing this course, students will know how to use social media productively, apply analytical techniques, and evaluate new social analysis tools and platforms.

Instructor Bio
Dr. Eui-Hong (Sam) Han is Director, Big Data & Personalization at Washington Post. Sam is an experienced practitioner of data mining and machine learning. He has in-depth understanding of analytics technologies and has experience of successfully applying these technologies to solve real business problems. At Washington Post, he is leading a team to build an integrated Big Data platform to store all aspects of customer profiles and activities from digital and print circulation, social media, metadata of content, and business data. His team builds an infrastructure, tools, and services to utilize the integrated data from the platform to provide personalized contents and experience for users, provide complete and linked data for business analytics and reporting, increase profit for Digital Ad Ops, and help newsrooms and other business units to make data-driven decisions. Prior to joining Washington Post, he led Big Data practice at Persistent Systems. He has engaged in Big Data analytics projects by combining his analytics background with Big Data technologies. He started Machine Learning Group at Sears Holdings Online Business Unit, and led several researchers and engineers for delivering analytical solutions for Data Quality, Search/Browse Optimization, Personalized Recommendations, Social Media Analysis, and Web Intelligence. His expertise includes data mining, machine learning, information retrieval, and high performance computing. He holds PhD in Computer Science from University of Minnesota.

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Mary Byerley

Mary Byerley serves in the Office of Student Success and Academic Services for the School of Business at George Mason University.
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