Syllabus Social Computing - (414451) Credit Scheme : Examination Scheme : 03 Credits Mid_Semester : 30 Marks End_Semester : 70 Marks Unit I Introduction to Social Media The foundation for analytics, social media data sources, defining social media data, data sources in social media channels, Estimated Data sources and Factual Data Sources, Public and Private data, data gathering in social media analytics. (Chapter - 1) Unit II Network Measures Centrality : Degree Centrality, Eigenvector Centrality, Katz Centrality, PageRank, Betweenness Centrality, Closeness Centrality, Group Centrality. Transitivity and Reciprocity, Balance and Status, Similarity : Structural Equivalence, Regular Equivalence Information Diffusion in social media : Herd Behaviour, Information Cascades, Diffusions in Cascades, Epidemics. (Chapter - 2) Unit III Mining in Social Media Data Mining in Social Media : Motivations for Datamining in Social Media, Data mining Methods for Social Media, Data Representation, Data mining - A Process, Examples - Social Networking Sites, The Blogosphere Text mining in Social Networks : Keyword Search, Query Semantics and Answer Ranking, Keyword search over XML and relational data, Keyword search over graph data, Classification Algorithms, Clustering Algorithms, Transfer Learning in Heterogenous Networks. (Chapter - 3) Unit IV Influence and Homophily Influence and Homophily : Measuring Assortativity, Influence, Homophily, Distinguishing Influence and Homophily : Shuffle test, Edge-Reversal Test, Randomization Test. (Chapter - 4) Unit V Social Media Behavior Recommendation in social media : Challenges, Classical Recommendation Algorithms, Recommendation using Social Context, Evaluating Recommendations, Behaviour Analytics : Individual Behaviour, Collective Behaviour. (Chapter - 5) Unit VI Case Study Mining Google+ : Overview, Exploring Google+ API, A Whiz bang Introduction to TF-IDF, Query human Language Data with TF-IDF. Mining Web pages : Scraping, Parsing, and crawling Web, Discovering Semantics by Decoding syntax, Entity-Centric Analysis, Quality of Analysis for Processing Human Language Data. (Chapter - 6)
