Social and Information Network Analysis
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Social and Information Network Analysis Syllabus — Unit-wise Content
The official GTU curriculum for Social and Information Network Analysis (subject code 3174209) as prescribed for AI & ML · Semester 7 divides the course into 5 units, covering 7 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (3174209)Unit 1 INTRODUCTION
- Introduction to Semantic Web: Limitations of current Web - Development of Semantic Web - Emergence of the Social Web - Social Network analysis: Development of Social Network Analysis - Key concepts and measures in network analysis - Electronic sources for network analysis: Electronic discussion networks
- Blogs and online communities - Web-based networks - Applications of Social Network Analysis
Unit 2 MODELLING, AGGREGATING AND KNOWLEDGE REPRESENTATION
- Ontology and their role in the Semantic Web: Ontology-based knowledge Representation - Ontology languages for the Semantic Web: Resource Description Framework - Web Ontology Language - Modelling and aggregating social network data: State-of-the-art in network data representation - Ontological representation of social individuals - Ontological representation of social relationships - Aggregating and reasoning with social network data - Advanced representations. 2021 - 22 Subject Code : 3174209 Subject Name : Social and Information Network Analysis
Unit 3 EXTRACTION AND MINING COMMUNITIES IN WEB SOCIAL NETWORKS
- Extracting evolution of Web Community from a Series of Web Archive - Detecting communities in social networks - Definition of community - Evaluating communities - Methods for community detection and mining - Applications of community mining algorithms - Tools for detecting communities social network infrastructures and communities - Decentralized online social networks - Multi-Relational characterization of dynamic social network communities
Unit 4 PREDICTING HUMAN BEHAVIOUR AND PRIVACY ISSUES
- Understanding and predicting human behaviour for social communities - User data management - Inference and Distribution - Enabling new human experiences - Reality mining - Context - Awareness - Privacy in online social networks - Trust in online environment - Trust models based on subjective logic - Trust network analysis - Trust transitivity analysis - Combining trust and reputation - Trust derivation based on trust comparisons - Attack spectrum and countermeasures
Unit 5 VISUALIZATION AND APPLICATIONS OF SOCIAL NETWORKS
- Graph theory - Centrality - Clustering - Node-Edge Diagrams - Matrix representation - Visualizing online social networks
- Visualizing social networks with matrix-based representations - Matrix and Node-Link Diagrams - Hybrid representations - Applications - Cover networks - Community welfare - Collaboration networks - Co-Citation networks
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