Syllabus - Social Networks (IT 703 (C))

Information Technology

Social Networks (IT 703 (C))

VII-Semester

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 - MultiRelational 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.

Course Objective

The objective of this course is to focus on the importance of social network analysis and to enhance skills of students for analyzing social media and networking data.

Course Outcome

["Understand the importance of social media and networks", "Have skills for analyzing social media and networking data", "Visualize social networks", "Create real-life case studies using social media data", "Plan and execute a small-scale network analysis project."]

Practicals

Reference Books

  • Ajith Abraham, Aboul Ella Hassanien, Václav Snášel, ―Computational Social Network Analysis: Trends, Tools and Research Advances‖, Springer, 2012

  • Borko Furht, ―Handbook of Social Network Technologies and Applications‖, Springer, 1st edition, 2011

  • Charu C. Aggarwal, ―Social Network Data Analytics‖, Springer; 2014

  • Giles, Mark Smith, John Yen, ―Advances in Social Network Mining and Analysis‖, Springer, 2010.

  • Guandong Xu , Yanchun Zhang and Lin Li, ―Web Mining and Social Networking – Techniques and applications‖, Springer, 1st edition, 2012

  • Peter Mika, ―Social Networks and the Semantic Web, Springer, 1st edition, 2007.

  • Przemyslaw Kazienko, Nitesh Chawla,‖Applications of Social Media and Social Network Analysis‖, Springer,2015

  • Maksim Tsvetovat and Alexander Kouznetsov , “Social Network Analysis for Startups”, O’Reilly Media, 2011.

  • Charles Kadushin, “Understanding Social Networks”, Oxford University Press, 2012

  • Social Network Analysis: Theory and Applications