English   Danish

2013/2014  BA-SMA  Social Media Analytics

English Title
Social Media Analytics

Course information

Language English
Exam ECTS 7.5 ECTS
Type Elective
Level Bachelor
Duration One Semester
Course period Autumn
Time Table Please see course schedule at e-Campus
Study board
Study Board for BSc/MSc in Business Administration and Information Systems, BSc
Course coordinator
  • Lectures, Exercises, Demos, and Project Report Grading
    Abid Hussain - Department of IT Mangement (ITM)
  • Course Coordinator
    Ravi Vatrapu - Department of IT Mangement (ITM)
Administrative contact person is Jeanette Hansen at ITM (jha.itm@cbs.dk).
Main academic disciplines
  • Information Systems
  • Communication
  • Marketing
  • Methodology
Last updated on 14-11-2013
Learning objectives
After the course the student should be able to:
  • Characterize the field of social media analytics
  • Explain the different conceptual and methodological approaches to analyzing social data
  • Analyze and apply methods and tools for Social Graph Analytics for a given organization
  • Analyze and apply methods and tools for Social Text Analytics for a given organization
  • Define and develop social media metrics and key-performance indicators across a range of dimensions for a selected organization
Course prerequisites
Prior knowledge of business intelligence/business analytics is desired but not required
Examination
Project Exam:
Examination form Home assignment - written product
Individual or group exam Individual
Size of written product Max. 15 pages
Assignment type Project
Duration Written product to be submitted on specified date and time.
Grading scale 7-step scale
Examiner(s) One internal examiner
Exam period December/January
Make-up exam/re-exam
Same examination form as the ordinary exam
Description of the exam procedure
The project report should be in accordance with the CBS policies and guidelines for formatting, page length and number of characters available on the CBS LEARN Project Post.

Structure
Project reports MUST follow the ITMRD structure as detailed below.

 I: Introduction:
Introduce the topic, motivations for studying the topic, how it is relevant to Internet Marketing, why it is important, what is the main problem/question.

T: Theoretical Framework:  
Make the connections to relevant theory and provide conceptual grounds for your paper. Draw from theories from the course literature and from your other courses. Please cite the relevant articles and reports from the course literature, from your previous courses that and from your own search

M: Methodology:
How you decided to study the above topic and answer the questions posed above. Basically, why and how you did what you did to address the questions and/or answer the problems in Introduction.

R: Results:
Present the data that you collected, how the data was analysed, and the main findings. In case of theoretical work or literature reviews, you report the results of your theorizing and the findings of your literature survey.

D: Discussion:  
Discuss your results in this section. This section should answer the “so what” questions. Relate the results back to the topic, questions and problems mentioned in the Introduction. Also discuss if the methods used limited and/or biased the results you obtained. Basically, interpret your results. Say why what you did and how you did it and what you ultimately found “matters”. Draw the big picture, generate implications for theory and practice if there are any.
Finally conclude.

Section Weights
Introduction: 10
Theoretical Framework: 20
Methodology: 20
Results: 20
Discussion: 30
Total:          100

Grading Criteria
Marks (Grade)
=>90 (12)    
80-89(10)    
70-79 (7)    
60-69 (4)    
50-59 (2)    
40-49 (0)    
<=39 (-3)
Course content and structure
The subject of the course is social media analytics, with special attention to social networking and micro-blogging sites that are expected to influence online marketing practices over the next few years.

The content of the course is structured in a number of themes, for example:
• Social Computing and Social Media
o Criteria of Effectiveness
o Social Data:
o Social Graph Analytics
o Social Text Analytics
o Metrics & KPIs
o Techniques (e.g., Social Network Analysis, Semantic Analysis, Online Sentiment Analysis)
o Tools (e.g., SODATO, Pagelever, Social Bakers, facebok Insights, Crowdbooster)
o Social Graph and the Brand
o Emerging Organizational Role of Social Media Analysts
o Case Studies
Teaching methods
Lectures, Exercises, and Demos
Expected literature
Textbook:
Lovett, J. (2011). Social Media Metrics Secrets: Wiley.

  Articles
Vatrapu, R. (in press/2013). Understanding Social Business. In K.B. Akhilesh (Ed.), Emerging Dimensions of Technology Management. Springer.
Last updated on 14-11-2013