GRA 6843 Applying Social Media in Management Decisions
GRA 6843 Applying Social Media in Management Decisions
(Max 30 students each semester)
Social media have become ubiquitous in the last years. Facebook now has more monthly users than the biggest nation in the world has inhabitants and new platforms and services are popping up weekly. At the same time, research is increasingly investigating social media from a variety of angles both with classical social science methods such as surveys, interviews and content analysis, and new methods. These new methods include, among others, big data studies of user interactions, sentiment analysis, digital ethnography and the investigation and visualization of geo-spatial data via mapping. Insights from such social media analysis are an increasingly important success factor in todays business environment.
In this course, the general objective is to provide master students with a solid grasp of the Digital Methods approach, both in theoretical and practical terms. Studying online and social media via a Digital Methods lens allows to come up with innovative new research questions, to develop an own Digital Methods project and to apply specifically developed Digital Methods tools to answer relevant managerial and social questions. The emphasis of the class will be on applications and interpretation of the results from locating and collecting data and analyzing information.
Students are expected to have taken classes in statistics and have working knowledge of MS Excel and SPSS. We expect students to have a solid grasp of the English language as well as a strong interest in the issues at hand, and to actively participate in class.
During the course there will be an intensive study trip to Berlin. Students must be aware that cost for and connected with the trip is not covered by BI Norwegian Business School and students are expected to cover this cost themselves.
- Participants will obtain an understanding for the role of data and social media in todays world, and will get acquainted with up-to-date methodology to plan and to frame research questions, both for practical as well as for academic endeavors.
- Participants will learn new approaches of gathering data from online and social media and to extract insights from these data, using sophisticated software-supported techniques such as social network analysis, link analysis and sentiment analysis.
- Strong emphasis will be laid on methodological concerns and a fundamental understanding for the nature of data combined with hands-on trainings and discussion of tools and sources for insights generation.
- Participants will also work with business model development frameworks and get acquainted with start-ups and social ventures. They will combine the methodological knowledge acquired about analysing social media data with conceptual expertise about start-ups and business models in order to develop a social business idea.
Participants will get to know effective ways to derive and present findings from data, ranging from visualization to insights-driven argumentation, such as:
- conducting perception studies and identifying key influencers
- using software to analyze Google, Twitter, Facebook and applying social media analytics
- aggregating and visualizing insights
Participants will work with innovative approaches of developing business ideas, based on the value proposition design framework and inspired by their data analysis. In particular, they will:
- learn how to develop stakeholder personas
- think about conrete benefits of a business idea (customer gains)
- think about concrete disadvantages and problems of a business idea (customer pains)
- develop strategies to enhance the benefits (customer gains) and remove the disadvantages (customer pains)
Strong emphasis will be laid on:
- developing a critical understanding of current trends in social media development and design, especially regarding the role of machine learning, data science and algorithms
- appreciating the role of both big and small data
- understanding the role of the social sciences in investigating social media and applying model-based and theoretically guided principles to analyze them
- developing expertise on social businesses, particularly in a start-up context
- applying business model development frameworks to develop tangible ideas
1) Introduction: Digital Methods, Big Data and Social Media
An overview of the Digital Methods paradigm, and a showcase of current examples in the form of interesting research and company studies is given. Students will obtain insights into the way of thinking of Digital Methods and get a first grasp of practical questions and challenges that can occur when conducting research with social media.
2) Social Ventures and Value Propositions
The context of social ventures and start-ups - an important element for the course in general and the assignment in particular - is introduced. Students will familiarize themselves with examples and conceptual approaches to the topic of start-ups in general and social ventures in particular. They will apply the value proposition design method to get structured insights into the eco-system of social ventures.
3) Personas
In this session, students will get acquainted with the design of stakeholder personas. This qualitative approach serves to illustrate potential customers and stakeholders in a vivid and intuitive way. Students will learn about the conceptual underpinnings of personas, the application - with concrete cases and examples - and they will develop their own personas in an interactive exercise.
4) Hands-on Digital Methods I: Data Collection and Descriptive Analysis
The first session on digital methods deals with the collection and analysis of social media data. A large focus is on Twitter due to the availability of the data and user-friendly, free software tools. The data collection is described in context and students are introduced to aspects such as APIs and their policies. For the data analysis, students will use visualization techniques and software to get insights from the data, for example regarding frequencies, temporal patterns and different types of tweets/posts.
5) Hands-on Digital Methods II: Social Network Analysis and sentiment Analysis
The second session on digital methods gives an introduction into more advanced ways of analyzing social media data. While social network analysis allows for the relational analysis of social media data (for example, who follows who? where are influencers?), sentiment analysis covers the positivity or negativity of social media content. With sentiment analysis, we will also discuss the topic of social media content analysis more broadly. The students will get acquainted to Gephi for social media analysis, and with Sentistrength for sentiment analysis.
6) Project Work and Guest Lectures
In these sessions, students will work hands-on with social media data to learn ways to follow relevant research questions, discovering what different interest groups are taking about, analyzing social media pages, examining friendships and getting to understand web site traffic and interconnectedness. Thus, the tools and methods discussed in the previous session will be put into practice. Moreover, guest lectures will deepen the content from the previous sessions.
7) Project Presentation and Discussions
The students will present their projects and the current status of their reports to the group. The assignments will be discussed critically with the other participants and the instructors of the course. The main findings, implications and challenges during the research project are addressed, trying to condense the key learning across the groups.
Issuecrawler, Webometric, Gephi, Sentistrength, brandwatch will be used (no extra costs for the students).
The course aims at combining formal lectures with a case teaching approach. The course will consist of the following elements:
- Formal lectures for basics of the topics and to provide a conceptual framework;
- Case studies for deepening knowledge of the research process, as well as for applying theoretical knowledge to real-world situations;
- Guest lectures by practice experts in order to gain insights in their roles/activities and experiences.
The course includes a study tour abroad. Students must be aware that cost for and connected with the trip is not covered by BI Norwegian Business School and students are expected to cover this cost themselves.
Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class that is not included on It's learning or text book.
All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
| Assessments |
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Exam category: Submission Form of assessment: Written submission Weight: 100 Grouping: Group (2 - 3) Duration: 1 Semester(s) Exam code: GRA68431 Grading scale: ECTS Resit: Examination when next scheduled course |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.
To gain attestation, the participants will be asked to form teams of maximum 3 students. They work on a task over the course of the semester. Students are expected to produce a report on a set methodological topic (no longer than 20 pages). To do so, students will gather primary social media data on a topic, relying on the approaches outlined in class (descriptive analysis of social media data, social network analysis, sentiment analysis).