Social Network Analysis
The structure and organization of real-world systems ¿ physical, ecological, and social ¿ is often better represented through the set relationships between its building. In fact, many dynamical problems that occur on social systems ¿ such as disease spreading, opinion formation, information cascades, and behavior adoption ¿ can only be truly understood after one considers the underlying structure of relationships between its agents/actors. In that sense, Network Science presents a powerful set of methodologies to abstract and think about network problems, and to extract meaningful and actionable information for a wide range of applications.
In the Social Network Analysis curricular unit, we will focus on the vast accumulated knowledge that resulted from the application of Network Science methods to study problems in the realm of Social Sciences. Hence, during the 7 weeks of this Curricular Unit students will learn about the fundamentals of Network Science, understand how it can be used in social sciences, and understand how social networks shape the diffusion of different types of information. A special focus will be placed on applications to Marketing such as Influencer detection and individual targeting.
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.
Additional reading materials will be shared in Moodle;
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 (50%)
EE2 - Final theoretical exam (50%).
The first grading season is dedicated to continuous evaluation, which includes the following components:
- Exam (30%) ¿ Final Theoretical exam to take place during the 8th week of the first semester. The exam consists of 40 multiple-choice questions and will have a duration of 45 minutes. Correct answers count 0.5 points, and incorrect answers discount 0.2 points. More details will be shared with the students during the classes;
- Class Activities (20%) ¿ Active participation in class activities developed during the duration of the curricular unit;
- Group Activity (50%) ¿ Oral presentation of a scientific manuscript of the student¿s choice. Students are expected to show their ability to comprehend the contribution of a manuscript, be able to identify the novelty, its impact on Social Sciences (Marketing in particular), identify aspects for improvement, and communicate to their peers their findings. Groups should have a maximum size of 4 students. Students will be assessed by the clarity of their communications (40%), the correctness of the methods presented (30%), and the relatedness of the topic to the syllabus of the curricular unit (30%). Slides should follow the template shared on Moodle. The delivery consists of a PDF copy of the selected manuscript, the deck of slides in PDF format, and a short 250-word abstract to be submitted through Moodle. More details will be shared during the classes (e.g., presentation day, format, and duration).
The second grading season will take place in January and consists of a multiple-choice exam. The exam consists of 40 multiple-choice questions and will have a duration of 45 minutes. Correct answers count 0.5 points, and incorrect answers discount 0.2 points.
The curricular unit is organized into 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
- Especialização em Data Science for Marketing
- Especialização em Digital Marketing and Analytics
- Specialization in Knowledge Management and Business Intelligence
- Specialization in Information Systems and Technologies Management
- Especialização em Marketing Intelligence
- Specialization in Marketing Intelligence
- Especialização em Marketing Research e CRM
- Specialization in Marketing Research and CRM
- Laboral - Especialização em Digital Marketing and Analytics
- Specialization in Knowledge Management and Business Intelligence – Working Hours Format
- Specialization in Information Systems and Technologies Management - Working Hours Format
- Laboral - Especialização em Marketing Intelligence
- Specialization in Marketing Intelligence - Working Hours Format
- Mestrado em Data-Driven Marketing
- 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
- PostGraduate in Marketing Intelligence
- PostGraduate Marketing Research e CRM
- PostGraduate in Enterprise Information Systems