Social Network Analysis
The structure and organization of real-world systems ¿ physical, ecological, and social ¿ are better represented through the set relationships between its building blocks (e.g., individuals). Indeed, many dynamical problems that occur on social dynamics ¿ such as disease spreading, opinion formation, behavior adoption ¿ require a representation of a social system as the sum of all embedded social relationships. In that sense, Network Science has become a valuable resource for analyzing such structures and provide a more relevant picture of the underlying organization of many complex systems.
In this Social Network Analysis curricular unit we will cover a theoretical introduction to network science, and its many applications in the characterization of social structures. Moreover, we will learn how social networks shape the diffusion of different types of information and can lead to complex emergent phenomena. A special focus will be placed into Social Sciences and Marketing applications.
The SNA curricular unit will have a strong active learning component. As such students are expected to actively participate in the class and read the recommended materials prior to each class. Practical classes will be delivered by the end of the seventh weeks and provide students with the hands-on experience of the theoretical concepts lectured during the first 5 weeks.
Flávio Luís Portas Pinheiro
Weekly - Available soon
Total - Available soon
Portuguese. If there are Erasmus students, classes will be taught in English
The curricular unit does not have technical enrollment requirements.
Classes will be taught in English, and as such students are expected to have a good comprehension and communication of English.
- Barabási, Albert-László. Network science. Cambridge University Press, 2016.
- Easley and Kleinberg, Networks, Crowds, and Markets: Reasoning about a highly connected world. Cambridge Univ. Press, 2010.
- Newman, Networks: An introduction. Oxford Univ. Press, 2010.
- Jackson, Social and Economic Networks. Princeton Univ. Press, 2008.
- Selected scientific manuscripts that will be shared by the teaching staff.
The curricular unit combines a mix of theoretical and practical lessons with a strong focus on active learning. During each session, students will be introduced to new concepts and methodologies, case studies, and practical examples. Active learning activities (debates, quizzes, mud cards, compare and contrast) will place students at the center of the classroom so that each takes an active role in the discussion and foster the learning process. Computer activities will take place whenever appropriate. For instance, students will build and analyze the class friendship network and thus get some hands-on experience and familiarity with the topics of the course.
EE1 - Participation in classroom activities (60%)
EE2 - Final theoretical exam (40%).
To successfully finish this curricular unit, students need to score a minimum of 9.5 points. The grading is divided into two seasons. Attendance in the second is optional for students that passed the curricular unit in the first season and can be used to improve their grade.
The first grading season is dedicated to continuous evaluation, which includes the following components:
- Quizzes (40%) ¿ Set of multiple-choice questions at the start of each Lecture. Quizzes will be performed on Socrative. Students can answer the quiz using their smartphones or computer laptop as long as they have an internet connection and a web browser. Login details will be shared in Moodle during the first week of classes. Students are incentivized to discuss with their colleagues during the quiz;
- Final Exam (40%) ¿ The Final Exam will take place during the 8th week of the first semester and consists of a 40-question multiple-choice exam. Correct answers count 0.5 points towards the final mark, and incorrect answers discount 0.2 points.
The second grading season will take place in January and consists of a multiple-choice exam. The Exam consists of 40 questions. Correct answers count 0.5 points, and incorrect answers discount 0.2 points.
The curricular unit is organized in three Learning Units (LU):
LU0. Introduction to Network Science
LU1. The role of network science in the diffusion of information and behavioral adoption
LU2. Application of network science to marketing
Programs where the course is taught:
- Specialization in Information Analysis and Management
- Specialization in Risk Analysis and Management
- Specialization in Knowledge Management and Business Intelligence
- Specialization in Information Systems and Technologies Management
- Specialization in Marketing Intelligence
- Specialization in Marketing Research and CRM
- Specialization in Knowledge Management and Business Intelligence – Working Hours Format
- Specialization in Information Systems and Technologies Management - Working Hours Format
- Specialization in Marketing Intelligence - Working Hours Format
- Post-Graduation in Information Analysis and Management
- Post-Graduation Risk Analysis and Management
- PostGraduate in Data Science for Marketing
- PostGraduate in Digital Enterprise Management
- PostGraduate Digital Marketing and Analytics
- PostGraduate in Information Management and Business Intelligence in Healthcare
- Post-Graduation in Knowledge Management and Business Intelligence
- Post-Graduation Information Systems and Technologies Management
- Post-Graduation in Marketing Intelligence
- Post-Graduation Marketing Research e CRM
- PostGraduate in Enterprise Information Systems