OUR ACADEMIC DEPARTEMENTS |
Lesson details
SOCIAL NETWORK ANALYSIS: A TECHNIQUE FOR STUDYING AN INTERCONNECTED WORLD | |||
2018-2019 | EnIESEG School of Management
(
IÉSEG
)
| ||
Class code : | 1819-IÉSEG-M1S1-MIS-MA-EI43UE | MANAGEMENT OF INFORMATION SYSTEMS |
Level | Year | Period | Language of instruction |
---|---|---|---|
Master | 1 | S1 | EnEnglish |
Academic responsibility | F.BOLICI |
---|---|
Lecturer(s) | Francesco BOLICI |
- This class exists in these courses :
- IÉSEG > IESEG Degree - Programme Grande École > Semester 1 > 2,00 ECTS
Prerequisites
Students who sign up for this course should not have particular prerequisites except a desire to understand how new models are emerging in networked environment. Students should show an active participation in class, as well as the ability to ask critical questions and to work in a team. Basic knowledge of the key concepts of management studies, organization design and information system can help.
Learning outcomes
At the end of the course, the student should be able to:
- learn the crucial concepts of organizational network models, their advantages and disadvantages both in social and business life
- understand the basic concepts of Social Network Analysis (SNA) method
- learn how to use the key indicators of SNA
- apply the foundations of SNA to business cases and also to social phenomena
- use basic functions of SNA tools as Gephi, Pajeck, Ucinet, etc.
This course will help the student to address those and other issues, and to understand how the network environment influences not only their social life, but also the business models of the most active companies. The main aim of the course is to introduce the basics of the Network Analysis methodology and tool.
Course description
The course will address the topic of how network models are pervading actual business and social life. Social network analysis (SNA) is the use of network theory to analyze social networks. The course aims introduce SNA as one of the most innovative and successful fields of management research. SNA is a method for representing and analyzing the structure of relationships among nodes of a network.
How many friends do you have on Facebook? How do you act in the networks of social relationships? How many followers on Twitter? Are you a LinkedIn user? How many links can you manage? What are the structural characteristics of your social network? Which kind of network relationship could provide the best chances to find what you are looking for? The same kind of questions can be applied to the business environment in order to understand how companies are dealing with the increasing number of relationships they have to manage (alliances, customers, suppliers, employees, etc.).
WARNING : SNA is a modeling method and a analytical technique, so it can be applied also to online social networks as Facebook, Twitter, etc. but it is not limited to them.
Class type
Class structure
Group discussion, visual presentation, group exercises, individual exercises, and real-world case studies tailored to each topic. Learning is further reinforced as attendees work on carefully selected case studies and exercises which incorporate the core concepts presented in the lectures. People learn the best by being engaged, so we orient the course to engage the participants throughout the learning experience.
Type of course | Numbers of hours | Comments | |
---|---|---|---|
Independent work | |||
Research | 2,00 | ||
Independent study | |||
Estimated personal workload | 8,00 | ||
Group Project | 8,00 | ||
Face to face | |||
Interactive class | 8,00 | ||
lecture | 8,00 | ||
Total student workload | 34,00 |
Teaching methods
- Interactive class
- Lecture
- Presentation
- Project work
Assessment
The assessment is both at individual level (final exam and individual participation, also contributing to the wiki page of the course) and group level (team-project).
Type of control | Duration | Number | Percentage break-down |
---|---|---|---|
Final Exam | |||
Written exam | 1,50 | 1 | 40,00 |
Others | |||
Individual Project | 8,00 | 1 | 40,00 |
Continuous assessment | |||
Participation | 16,00 | 1 | 20,00 |
TOTAL | 100,00 |
Recommended reading
- A set of articles will be posted on the course website (www.francescobolici.com) around two weeks before the beginning of the course -
Internet resources
* This information is non-binding and can be subject to change