Download A real-world network is modeled in the computer as a graph: ▫ A set of nodes (or vertices, singular vertex). ▫ Some nodes are connected by ...
Download 2 Oct 2013 ... Network Analysis. Applications of networks in Psychology and beyond. Sacha Epskamp. University of Amsterdam. Department of Psychological ...
Download A real-world network is modeled in the computer as a graph: ▫ A set of nodes (or vertices, singular vertex). ▫ Some nodes are connected by edges (or links).
Download 2 Oct 2013 ... Network Analysis. Applications of networks in Psychology and beyond. Sacha Epskamp. University of Amsterdam. Department of Psychological ...
Download A real-world network is modeled in the computer as a graph: ▫ A set of nodes (or vertices, singular vertex). ▫ Some nodes are connected by edges (or links).
Download A real-world network is modeled in the computer as a graph: ▫ A set of nodes (or vertices, singular vertex). ▫ Some nodes are connected by edges (or links).
Download A real-world network is modeled in the computer as a graph: ▫ A set of nodes (or vertices, singular vertex). ▫ Some nodes are connected by edges (or links).
Download A real-world network is modeled in the computer as a graph: ▫ A set of nodes (or vertices, singular vertex). ▫ Some nodes are connected by edges (or links).
Download 2 Oct 2013 ... Network Analysis. Applications of networks in Psychology and beyond. Sacha Epskamp. University of Amsterdam. Department of Psychological ...
Download A real-world network is modeled in the computer as a graph: ▫ A set of nodes (or vertices, singular vertex). ▫ Some nodes are connected by edges (or links).
Download A real-world network is modeled in the computer as a graph: ▫ A set of nodes (or vertices, singular vertex). ▫ Some nodes are connected by edges (or links).
Ohm's Law, Kirchhoff's Law, Node and Mesh Analysis, Network Theorem, Two Port ... Kirchhoff's Voltage Law. 5.3. Kirchhoff's Current Law. 6. Node and Mesh Analysis. 6.1. Node Analysis. 6.2. Mesh Analysis. 7. Network Theorems. 7.1. Linearity. 7.2. ....
Download Social network analysis (SNA) focuses on the structure of ties within a set of social ... For network analysis to be applicable, theory from sociology or other social.
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Network Analysis 10ES34 CITSTUDENTS.IN 1 PART – A UNIT 1: ... “Network analysis and Synthesis”, Franklin F. Kuo, Wiley International Edition, 3
Download Organizational Network Analysis (ONA) explained. Every organization has people (“nodes”) who serve as critical conduits for exchange of ideas and information.
Download Organizational Network Analysis (ONA) explained. Every organization has people (“nodes”) who serve as critical conduits for exchange of ideas and information.
Download Social network analysis (SNA) focuses on the structure of ties within a set of social ... For network analysis to be applicable, theory from sociology or other social.
Loop and node variable analysis, Waveform Synthesis-The Shifted Unit Step, Ramp and. Impulse Function, Waveform Synthesis, The Initial and Final Value Theorems, The Convolution. Integral. Module-II. IMPEDANCE FUNCTIONS AND NETWORK THEOREMS: The Conce
Network Analysis 10ES34 CITSTUDENTS.IN 1 PART – A UNIT 1: Basic Concepts: Practical sources, Source transformations, Network reduction using Star – Delta
Download Social network analysis (SNA) focuses on the structure of ties within a set of social ... For network analysis to be applicable, theory from sociology or other social.
Download Social network analysis (SNA) focuses on the structure of ties within a set of social ... For network analysis to be applicable, theory from sociology or other social.
Download Social Network Analysis by Olivier Serrat. Rationale. The information revolution has given birth to new economies structured around flows of data, information, ...
Download 1) Social Network Theory & Analysis. 2) Social Network Influences on Behavior. ( SNA of Behavior Change). 3) Social Network Analysis for Program.
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Network Analysis
CS102 Spring 2018
Network Analysis
CS102
Big Data Tools and Techniques § Basic Data Manipulation and Analysis Performing well-defined computations or asking well-defined questions (“queries”)
§ Data Mining Looking for patterns in data
§ Machine Learning
Over a specific type of data
Using data to build models and make predictions
§ Data Visualization Graphical depiction of data
§ Data Collection and Preparation Network Analysis
CS102
Networks A real-world network is modeled in the computer as a graph: § A set of nodes (or vertices, singular vertex) § Some nodes are connected by edges (or links) § Edges can be undirected or directed
Friends network (undirected)
Network Analysis
CS102
Example: Flight Routes
Network Analysis
CS102
Example: Flight Routes
Network Analysis
CS102
Example: Flight Routes
Network Analysis
CS102
Example: Disease Transmission
Network Analysis
CS102
Example: Food Chain
Network Analysis
CS102
Example: Criminal Networks
Network Analysis
CS102
Example: Science Citations
Network Analysis
CS102
Example: Retweets
Network Analysis
CS102
Example: Facebook Friends
Network Analysis
CS102
Other Examples § Electricity grid + other civil infrastructure § The brain + other biological structures § Organizations and organizational behavior § Spread of memes, other social phenomena § And many, many more …
Network Analysis
CS102
Network Analysis Properties specific to graph structure § Basic Data Manipulation and Analysis Asking well-defined questions
§ Data Mining Looking for patterns
Today: a few examples
§ Machine Learning Building models, making predictions
§ Data Visualization Graphical depiction
§ Data Collection and Preparation Network Analysis
CS102
Properties of Undirected Graphs Density of graph # of edges
________________________
# of possible edges
Network Analysis
CS102
Properties of Undirected Graphs Shortest paths in graph Shortest distance between given pair of nodes
“Six degrees of separation” (Four in Facebook)
Network Analysis
CS102
Properties of Undirected Graphs Diameter of graph Maximum shortest path in graph
Network Analysis
CS102
Properties of Undirected Graphs Cliques in graph Sets of fully-connected nodes
Network Analysis
CS102
Properties of Undirected Graphs Closeness centrality of a node in a graph Average shortest distance to all other nodes (inverted so higher is “better”)
Network Analysis
CS102
Properties of Undirected Graphs Betweenness centrality of a node in a graph Number of shortest paths the node lies on
Network Analysis
CS102
Directed Graphs
§ In-degree - How many “followers” § Out-degree - How many “following” § Reciprocity - How often links are bidirectional § Cycles
Network Analysis
CS102
Labeled Graphs
Network Analysis
CS102
Other Analyses “Link Prediction” Predict future edges added to the graph
Friends (or Follows) recommendations
Network Analysis
CS102
Other Analyses “Community Detection” Sets of interlinked/similar nodes
Network Analysis
CS102
Other Analyses “Cascades” - Information propagation
