Measuring Social is an experiential learning class for graduate students across Carnegie Mellon. We bring in 5-7 corporate sponsors each semester (Spring and Fall) and they develop a project for the student teams to work on over the semester. Each project involves an element of measuring unstructured social data as well as providing recommendations based on its analysis. The class has been running since 2010 and we have done over 120 projects in the class for close to 100 different unique clients including Marriot, Google, Warner Bros., Sony PlayStation, Nike, Target, Ford, NYTimes, The Lincoln Center, American Express, The Gap, NBCUniversal, Microsoft, etc. We welcome graduate students from across CMU including Data Analytics, Public Policy, Entertainment and Arts Management, Business/Tepper, CS/HCI, ECE, English and Design. We socially engineer teams to add as much diversity as possible. Projects in the class vary from internal social network analysis to external client and community engagement tactics through analyzing social data from thematic strings, sentiment analysis, community segments etc. As an example, a team working with Marriott used ML models to understand and present benefit with deploying social influencers across different categories (fashion, travel, lifestyle) associated with brand recognition for their W hotel properties. Students teams have access to commercially available off the shelf software tools for social listening and social intelligence and we provide in class training. Students have reported many benefits associated with participating in the class including: Opportunity to work with students from across CMU with different experience/viewpoints, Engaging in a real world consultative project with a brand name company, Development of non-cognitive skills associated with problem solving, and An opportunity to develop and present recommendations/data models that in many cases get implemented by sponsoring organizations.
- Develop critical thinking associated with client needs and ambiguous problem statements
- Collect, organize and analyze unstructured social data in order to develop recommendations for project sponsors
- Understand social data patterns, social listening, semantic processing and apply data modeling techniques to make sense of large amounts of collected social data
- Develop project management skills on project execution, task delegation, relationship management, etc.
- Work effectively as a team and developing non-cognitiive skills associated with agility, preserverance and cooperation
- Understand the different issues surrounding social data including online community formation, data privacy, social analytics, social listening and intelligence, social influences, progpogation of disinformaiton, etc.
- Develop management consulting skills making sure that projects are executed on time and add value to project sponsors
None - tools and training provided in class