Course Details

Course Number: 94-823

Measuring Social

Units: 12

This class reflects an experiential learning environment where students will be placed into teams with students from across Heinz and CMU to work with clients on projects involving measuring social content and activity. Each semester (Spring and Fall), we bring in 7 companies to provide challenging projects for the student teams. Teams are provided with commercially available tools to listen to online social conversations, measure activity, assess different market segments, understand social influence and identify how information get disseminated across social channels. Previous sponsors have included: Under Armour, Netflix, Target, The Washington Post, HBO, Daimler, eBay, Google, AT&T, The Pittsburgh Steelers, etc. The class is designed to teach social analytics, consulting methodologies, critical thinking to weed through ambiguity, project management as well as team and relationship development. Lectures focus on how social is impacting different industries, culture and communication, as well as the future of work. Teams work with their clients throughout the semester and present their findings/deliverables during final presentations when all 7 sponsors come to CMU. In the past, teams have built social applications, social algorithms, experimental methodologies, crowdsourced campaigns and real time information dash boards for their clients. This class offers an opportunity for students interested in analyzing social data, working in a consultative fashion with actual clients on real issues, and learning about global issues associated with an increasingly social culture.

Learning Objectives:

• Understand the different components surrounding social including online communities, privacy, social analytics, companies and platforms, tools, etc.
• Develop project management office (PMO) focusing on project execution, task delegation, relationship management, etc.
• Apply knowledge in researching, developing and presenting recommendations
• Analyze unstructured data stores to determine pattern correlations

• Understand success metrics around social initiatives and be able to effectively communicate their applicability

Syllabus

Faculty:
Ari Lightman