Social Network Analysis

Course Information
TitleΑνάλυση Κοινωνικών Δικτύων / Social Network Analysis
CodeDWS105
FacultySciences
SchoolInformatics
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter
CoordinatorAthina Vakali
CommonYes
StatusActive
Course ID600016259

Programme of Study: PMS EPISTĪMĪ DEDOMENŌN KAI PAGKOSMIOU ISTOU (2018 éōs sīmera) MF

Registered students: 7
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses belonging to the selected specialization117.5

Programme of Study: PMS EPISTĪMĪ DEDOMENŌN KAI PAGKOSMIOU ISTOU (2018 éōs sīmera) PF

Registered students: 21
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses belonging to the selected specialization117.5

Class Information
Academic Year2019 – 2020
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Total Hours39
Class ID
600153649
Type of the Course
  • Scientific Area
Course Category
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
Prerequisites
General Prerequisites
Graph Theory, Algorithms, Probabilities
Learning Outcomes
1. Identification of social networks and related analysis methods 2. Construction and analysis tools for data that are not in network form (text, image, etc.) 3. Learning of important properties and process characteristics on networks like community detection, sentiment analysis, information diffusion, network robustness, etc.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
  • Generate new research ideas
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Centrality measures, network models (random) and characteristics (small world phenomena, power law distribution on various networks characteristics), mechanisms for network generation (preferential attachment), network robustness. Online social data sources, community detection, sentiment analytics basics, information diffusion, influence detection, fraud detection.
Keywords
centrality measures, network models, community detection, dynamic processes on networks
Educational Material Types
  • Slide presentations
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
Description
Use of online courses platform. Email communication and course announcements forwarding to students. Upload all course material (slides, projects, extra material).
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures39
Reading Assigment81
Project60
Written assigments45
Total225
Student Assessment
Description
The assessment criteria can be found in the webpage of the course. More specifically, the assessment consists of: 1. Writing of Research Paper (50%) 2. Presentation of Published Research Paper (20%) 3. Final Exam (30%)
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Exam with Extended Answer Questions (Summative)
  • Written Assignment (Summative)
  • Performance / Staging (Summative)
  • Written Exam with Problem Solving (Summative)
  • Report (Summative)
Bibliography
Additional bibliography for study
[1] Networks, Crowds, and Markets: Reasoning about a Highly Connected World - D. Easly και J. Kleinberg. http://www.cs.cornell.edu/home/kleinber/networks-book/ [2] Network Science - A.L. Barabasi. http://barabasi.com/book/network-science [3] Introduction to social network methods - R.A. Hanneman και M. Riddle. http://faculty.ucr.edu/~hanneman/nettext/
Last Update
30-05-2019