The constant availability and flood of data and content online presents consumers with the challenge of quickly classifying content and drawing their conclusions from it. As a byproduct of digitalization, consumers therefore increasingly need the ability to critically reflect on content they see online. Many current developments in the area of social media underline this need. For instance, consumers and companies alike are confronted with fake news, fake reviews, content produced by machine learning algorithms, or moral outcry, social firestorms, or cancel culture.

Despite the growing relevance of these phenomena, marketing scholars have only just begun to explore these moral dimensions of social media consumption.

This course is designed to sensitize the participants to how digital content might be biased – sometimes even independent of the intentions of the content producer – and can impair critical thinking when dealing with social media data and content.

This project-based applied course will

1. provide the theoretical foundations on critical thinking on the one hand and social media marketing on the other hand. The course draws on behavioral economics and the fundamentals of the psychology of critical thinking to give an overview of biases that are especially prevalent in social media consumption. In addition, we will cover the psychology behind virality of content and the what, why, and how of major current approaches, including management of paid, earned and owned social media channels.
    
2. apply the theoretical concepts to a relevant and current case in a group project. Stimulated by contemporary trends in social media, you will in teams of five choose and work on a current case example and prepare both a presentation and a written seminar paper of your case. You will break down the research questions underlying the case based on a literature search, craft a compelling story and create content to tell the story. The question you address should be very specific both with regard to content and format (e.g., you design a format for WU’s Kids University to educate about responsible social media usage; you develop training material to teach companies how to respond to social media firestorms). In a final session, you present your case, followed by a joint discussion. A written seminar paper is handed it after completion of the course.  

The aim of the course is to provide participants with essential thought-provoking impulses for a critical and responsible approach to social media management, both from a consumer as well as corporate perspective. By the end of the course, participants should be able to

• to understand the consumer psychological aspects behind virality of social media content and cognitive biases affecting digital consumer behavior
• to reflect critically on their own analytical thinking and social media consumption
• to be able to assess external information and analyses with regard to their credibility and quality
• communicate more effectively in their own argumentation and presentation of results

In addition you will have developed your professional skills in developing a synthesis and story from a research question, creative thinking, and working in teams.

Participation in all sessions is mandatory. You may miss up to max. 20% of lecture hours, but please note that content is build-up in a modular way. Thus absences should be minimized to ensure your optimal learning outcomes.

• Self-study (reading of scientific articles and own researches of articles, blogs, and videos to prepare group project topic)
• Lectures and in-class discussions on theoretical foundations
• Team presentation of group project

Your grade will be the sum of the following components (max. 100 points)

• Project presentation: 40 pts
• Written project report: 40 pts
• Peer evaluation of group work: 10 pts
• Participation in class: 10 pts

Participation in class and the project presentation is graded at the individual level, while the written group project is graded at the group level. The peer review is used to assess the individual contribution of each group member to the group project.

Grades are as follows: 90 pts or more: 1 (= excellent), 80 pts or more: 2 (= good), 70 pts or more: 3 (=satisfactory), 60 pts or more: 4 (= sufficient), 59 pts or less: 5 (= fail).

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Ideally, students should have some prior experience with R / RStudio. Experience with Python is optional.