GRA 6843 Applying Social Media in Management Decisions

APPLIES TO ACADEMIC YEAR 2016/2017

GRA 6843 Applying Social Media in Management Decisions


Responsible for the course
Christoph Lutz, Christian Fieseler

Department
Department of Communication and Culture

Term
According to study plan

ECTS Credits
6

Language of instruction
English

Introduction
(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 today’s 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.


Learning outcome

  • Participants will obtain an understanding for the role of data and social media in today’s 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.

Acquired Skills
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
  • using data to define stakeholder personas
  • aggregating and visualizing insights

Reflection
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

Prerequisites

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 spesific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Compulsory reading
Books:
Osterwalder, A., Pigneur, Y., Bernarda, G., & Smith, A. 2014. Value Proposition Design: How to Create Products and Services Customers Want. John Wiley & Sons
Rogers, R. 2013. Digital Methods. Amsterdam University Press
Thelwall, M. 2004. Link Analysis: An Information Science Approach. Elsevier


Articles:
Bardhi, F., & Eckhardt, G. M. 2012. Access-based consumption: the case of car sharing. Journal of Consumer Research, 39(4), 881-898
Belk, R. W. 2013. Extended self in a digital world. Journal of Consumer Research, 40(3), 477-500
boyd, d. & Crawford, K. 2012. Critcial Questions for Big Data. Information, Communication & Society, 15(5), 662-679
Kane, G. C., Alavai, M., Labianca, G. J., & Borgatti, S. 2014. What’s different about social media networks? A framework and research agenda. MIS Quarterly, 38(1), 274-304
Mahrt, M., & Scharkow, M. 2013. The value of big data in digital media research. Journal of Broadcasting & Electronic Media, 57(1), 20-33
Marwick, A. E. 2011. I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience. New Media & Society, 13(1), 114-133
Mayer-Schonberger, V. & Cukier, K. 2013. A revolution that will transform how we live, work, and think. HMH Books
Rainie, L. & Wellman, B. 2012. Networked – The New Social Operating System. MIT Press.. (especially chapters “The New Social Operating System of Networked Individualism” (Chapter 1) and “A Day in a Connected Life” (Interlude))


Other:
During the course there may be hand-outs and other material on additional topics relevant for the course and the examination.


Recommended reading

Course outline

1) Introduction: Why Digital Methods?
An overview of the Digital Methods paradigm, and a showcase of current examples in the form of interesting research and company studies. 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) Living in a Data-Rich Society I: Opportunities
In this and the next session, students will get acquainted with some of the consequences of the spread of social media and big data, both in terms of opportunities and challenges. This session, in particular, will focus on new opportunities emerging with social media in different social fields: economic (new business models and ways of managing), political (new avenues for participation and deliberation), social (new opportunities for organizing and consuming, for instance in the context of online dating, Internet-mediated learning and communities of interest).

3) Living in a Data-Rich Society II: Challenges
While the previous session focused on the opportunities, this session will look at some of the specific challenges that come with the spread of social media and big data. Here, we look at issues such as privacy, addiction, discrimination, divides/polarization, cyberbullying and oversharing. The goal of this and the previous session is to reach a balanced view of the current discourses on social media and big data.

4) Theory, Theory, Theory
Students will learn about some current conceptual discussions and useful broad theories to analyze social media from an analytical point-of-view. Some prominent theories we will discuss include: affordances, public spheres and online deliberation, networked individualism.

5) Introduction to Digital Methods Tools I
In this first session on tools, students will get acquainted with tools and approaches to analyze more “traditional” and older structures of the Internet. Specifically, the session covers link analysis and search studies. The Issuecrawler software will be presented as well as the Webometric Analysis toolbox.

6) Introduction to Digital Methods Tools II
The second session on tools deals with approaches to analyze social media. Two methods are of particular interest: social network analysis and sentiment analysis. 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.

7-10) Project work
In these sessions, students will work hands-on with various new media 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.

11) Project Presentation and Discussions I
The students will present their projects to the group and discuss them critically with the other participants of the course. The main findings, implications and challenges during the research project are addressed, trying to condense the key learning across the groups.

12) Project Presentation and Discussions II
The students will present their projects to the group and discuss them critically with the other participants of the course. The main findings, implications and challenges during the research project are addressed, trying to condense the key learning across the groups.


Computer-based tools


Learning process and workload
A course of 6 ECTS credits corresponds to a workload of 160-180 hours.
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 to Berlin.


Examination
To gain attestation, the participants will be asked to form teams to work on two tasks over the course of the semester, in the form of take-home exercises. First, students are expected to produce a short state-of-the art overview on a set methodological topic (no longer than 15 pages). Second, students will gather primary data on a topic, relying on one of the approaches outlined in class. Students are expected to deliver a presentation on their findings and their applicability to a real-life problem, relying on the presentation techniques outlined in class and again reflecting on the generalizability of their findings (no longer than 20 minutes).


Form of assessment Weight Group size
Presentation 50% Group of max 3 students
Term paper 50% Group of max 3 students

Specific information regarding student assessment will be provided in class. This information may be relevant to requirements for term papers or other hand-ins, and/or where class participation can be one of several components of the overall assessment. This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded using points on a scale from 0-100. The final grade for the course is based on the aggregated mark of the course components. Each component is weighted as detailed in the course description. Students who fail to participate in one/some/all exam components will get a lower grade or may fail the course. You will find detailed information about the points system and the mapping scale in the student portal @bi. Candidates may be called in for an oral hearing as a verification/control of written assignments.

Examination code(s)
GRA 68431 continuous assessment accounts for 100 % of the final grade in the course GRA 6843.

Examination support materials
Not applicable
Permitted examination support materials for written examinations are detailed under examination information in the student portal @bi. The section on support materials and the use of calculators and dictionaries should be paid special attention to.

Re-sit examination
It is only possible to retake an examination when the course is next taught. The assessment in some courses is based on more than one exam code. Where this is the case, you may retake only the assessed components of one of these exam codes. All retaken examinations will incur an additional fee. Please note that you need to retake the latest version of the course with updated course literature and assessment. Please make sure that you have familiarised yourself with the latest course description.

Additional information
Honour code. Academic honesty and trust are important to all of us as individuals, and are values that are integral to BI's honour code system. Students are responsible for familiarising themselves with the honour code system, to which the faculty is deeply committed. Any violation of the honour code will be dealt with in accordance with BI’s procedures for academic misconduct. Issues of academic integrity are taken seriously by everyone associated with the programmes at BI and are at the heart of the honour code. If you have any questions about your responsibilities under the honour code, please ask. The learning platform itslearning is used in the teaching of all courses at BI. All students are expected to make use of itslearning.