CS6010 Social Network Analysis Syllabus Notes Question Papers 2 Marks with Answers Question Bank with answers Anna University
Anna University CS6010 Social Network Analysis Notes Syllabus 2 marks with answers Part A Question Bank with answers
Anna University CS6010 Social Network Analysis Syllabus Notes 2 marks with the answer is provided below. IT6006 Notes Syllabus all 5 units notes are uploaded here. here IT6006 Social Network Analysis Syllabus notes download link is provided and students can download the CS6010 Syllabus and Lecture Notes and can make use of it.
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CS6010 Social Network Analysis SYLLABUS REGULATION 2013
UNIT I 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 II 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.
UNIT III 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 IV 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 V VISUALIZATION AND APPLICATIONS OF SOCIAL NETWORKS
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 II 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.
UNIT III 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 IV 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 V 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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CS6010 Social Network Analysis Notes Syllabus Question Papers Question Bank
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