Social Network Analysis: A Non- Technical Introduction José Luis Molina Universitat Autònoma de Barcelona

Slides:



Advertisements
Similar presentations
Sesión 3. Análisis de redes sociales
Advertisements

Acculturation revisited A model of personal network change José Luis Molina Universitat Autònoma de Barcelona Miranda J. Lubbers Universitat Autònoma de.
Dr. Henry Hexmoor Department of Computer Science Southern Illinois University Carbondale Network Theory: Computational Phenomena and Processes Social Network.
Network Matrix and Graph. Network Size Network size – a number of actors (nodes) in a network, usually denoted as k or n Size is critical for the structure.
Lecture 5 Graph Theory. Graphs Graphs are the most useful model with computer science such as logical design, formal languages, communication network,
Introduction to Graph “theory”
Introduction to Social Network Analysis Lluís Coromina Departament d’Economia. Universitat de Girona Girona, 18/01/2005.
Social Network Analysis and Its Applications By Paul Rossman Indiana University of Pennsylvania.
Relationship Mining Network Analysis Week 5 Video 5.
Graphs Intro G.Kamberova, Algorithms Graphs Introduction Gerda Kamberova Department of Computer Science Hofstra University.
Centrality and Prestige HCC Spring 2005 Wednesday, April 13, 2005 Aliseya Wright.
Introduction to Graphs
Centrality Measures These measure a nodes importance or prominence in the network. The more central a node is in a network the more significant it is to.
CSE 222 Systems Programming Graph Theory Basics Dr. Jim Holten.
CSE 321 Discrete Structures Winter 2008 Lecture 25 Graph Theory.
Graph: Relations There are many kinds of social relations. For example: Role-based : brother of, father of, sister of, etc. : friend of, acquaintance of,
Network Measures Social Media Mining. 2 Measures and Metrics 2 Social Media Mining Network Measures Klout.
Graph Essentials Social Media Mining. 2 Measures and Metrics 2 Social Media Mining Graph Essentials Networks A network is a graph. – Elements of the network.
Social Media Mining Graph Essentials.
Social Networks Corina Ciubuc.
GRAPH Learning Outcomes Students should be able to:
Introduction to Network Theory: Basic Concepts
Graph Theoretic Concepts. What is a graph? A set of vertices (or nodes) linked by edges Mathematically, we often write G = (V,E)  V: set of vertices,
Class 2: Graph theory and basic terminology Learning the language Network Science: Graph Theory 2012 Prof. Albert-László Barabási Dr. Baruch Barzel, Dr.
Network properties Slides are modified from Networks: Theory and Application by Lada Adamic.
GRAPHS CSE, POSTECH. Chapter 16 covers the following topics Graph terminology: vertex, edge, adjacent, incident, degree, cycle, path, connected component,
Principles of Social Network Analysis. Definition of Social Networks “A social network is a set of actors that may have relationships with one another”
Representing and Using Graphs
A Clustering Algorithm based on Graph Connectivity Balakrishna Thiagarajan Computer Science and Engineering State University of New York at Buffalo.
7.1 and 7.2: Spanning Trees. A network is a graph that is connected –The network must be a sub-graph of the original graph (its edges must come from the.
Data Structures Week 9 Introduction to Graphs Consider the following problem. A river with an island and bridges. The problem is to see if there is a way.
It's a world-wide webby wonderland.. Graphs are often used to represent real-world information and real-world structures. Graph Theory was even invented.
Network theory David Lusseau BIOL4062/5062
Vertices and Edges Introduction to Graphs and Networks Mills College Spring 2012.
Lecture 13: Network centrality Slides are modified from Lada Adamic.
L – Modelling and Simulating Social Systems with MATLAB Lesson 6 – Graphs (Networks) Anders Johansson and Wenjian Yu (with S. Lozano.
Basic Notions on Graphs. The House-and-Utilities Problem.
COSC 2007 Data Structures II Chapter 14 Graphs I.
Most of contents are provided by the website Graph Essentials TJTSD66: Advanced Topics in Social Media.
The Structure of the Web. Getting to knowing the Web How big is the web and how do you measure it? How many people use the web? How many use search engines?
Introduction to Graph Theory
Graphs & Matrices Todd Cromedy & Bruce Nicometo March 30, 2004.
Homework #5 Due: October 31, 2000 Christine Kang Graph Concepts and Algorithms.
Basic properties Continuation
Graphs Upon completion you will be able to:
Selected Topics in Data Networking Explore Social Networks: Center and Periphery.
Class 2: Graph Theory IST402. Can one walk across the seven bridges and never cross the same bridge twice? Network Science: Graph Theory THE BRIDGES OF.
How to Analyse Social Network? Social networks can be represented by complex networks.
Informatics tools in network science
Chapter 9: Graphs.
Class 2: Graph Theory IST402.
Network Partition –Finding modules of the network. Graph Clustering –Partition graphs according to the connectivity. –Nodes within a cluster is highly.
Graphs. Graph Definitions A graph G is denoted by G = (V, E) where  V is the set of vertices or nodes of the graph  E is the set of edges or arcs connecting.
1 GRAPH Learning Outcomes Students should be able to: Explain basic terminology of a graph Identify Euler and Hamiltonian cycle Represent graphs using.
Lecture 20. Graphs and network models 1. Recap Binary search tree is a special binary tree which is designed to make the search of elements or keys in.
Fundamental Graph Theory (Lecture 1) Lectured by Hung-Lin Fu 傅 恆 霖 Department of Applied Mathematics National Chiao Tung University.
1 New metrics for characterizing the significance of nodes in wireless networks via path-based neighborhood analysis Leandros A. Maglaras 1 Dimitrios Katsaros.
Groups of vertices and Core-periphery structure
Basic Concepts Graphs For more notes and topics visit:
Social Networks Analysis
Graph theory Definitions Trees, cycles, directed graphs.
Agenda Lecture Content: Introduction to Graph Path and Cycle
Màster en Direcció d'Empreses / Master in Management
Network analysis.
Network Science: A Short Introduction i3 Workshop
Graph Theory.
Graphs All tree structures are hierarchical. This means that each node can only have one parent node. Trees can be used to store data which has a definite.
Graph Theory By Amy C. and John M..
Warm Up – Tuesday Find the critical times for each vertex.
GRAPHS.
Presentation transcript:

Social Network Analysis: A Non- Technical Introduction José Luis Molina Universitat Autònoma de Barcelona

Social Networks? Social networks as a metaphor of a complex world. Social networks as social networking platforms. Social networks as a way of empowerment of local actors for improving the current situation. Social networks as a Theory and Methods for studying social and cultural phenomena.

Network Science … An approach to the study of complexity …complexity Massive data about telecommunications, internet, biology, languages, political networks …

A long history... Moreno Sociometry (1934) Graph Theory (e.g. Harary 1963) Manchester School ( ) American Sociology (1976) INSNA & Computers & Interdisciplinariety

Who is working in SNA today...? The International Network for Social Network Analysis (INSNA)

Network data... For making visible relations among entities we have several options: Direct observation. Database of interactions. Asking (people): Name generators.

Sociograms...

... and Matrices AMRVGBEGJSJMMOCRPPGGJLMAFGDE AMG RVT GBB EG JSP JMF MOS CR PP GG JLM MAR FG DES

Sociocentric and egocentric networks … A sociocentric network is the outcome of a tie definition upon a list of nodes. – Normally a Tie Definition refers to an Institutional Setting (kin, workmates, friends, neighbours, cooperation with, report to …). An egonetwork is the subset of ties surrounding a given ego within the sociocentric network. So, sociocentric and egocentric networks refer to a single Institutional Setting.

Personal Networks A Personal Network is the outcome of using one or more Name Generator about Ego’ alters AND a Tie Definition for connecting her alters. If the list of alters is long enough (30 or more on average) all institutional settings in which ego participate will be represented (kin, friends, coworkers …)

Fundamentals … Vargas-Quesada, Benjamín, Moya-Anegón, Félix de (2007). Visualizing the Structure of Science. [pdf]pdf

Actor. In a social network graph, the actor may also be referred to as the node, vertex, or point. The actor does not necessarily have to represent a concrete unit or individual; it may also be a company, institution, or social group. Link. This may also be called a connection or line, and it may be directional ( arc ) or non- directional ( edge ), depending on whether it indicates the orientation – from one actor to another – or does not. Links may or may not be weighted.  Actor  In a social network graph, the actor may also be referred to as the node, vertex, or point. The actor does not necessarily  have to represent a concrete unit or individual; it may also be a company, institution, or social group.  Link  This may also be called a connection or line, and it may be directional or non-directional, depending on whether it indicates the orientation – from  one actor to another – or does not. In the first case, the link is called an the latter case it is non-directional or reciprocal. Links may or may not be weighted.  There is a special type of link, the self-link or loop, which is produced when an actor makes reference to itself.  Adjacent Actors  Actors that can be found in direct relation or connection via a link.  Neighborhood  Set of actors with which a given actor or node is adjacent.  Indirect Connections  Those made between non-adjacent nodes, through intermediary actors. They can also be called indirect links.  Path  This is the sequence of links and actors that connect two non-adjacent actors, without repeating any of them. The length of the path is determined  by the number of links.  Geodesic Distance  It is the shortest path between two nodes or actors of the network, and can also be denominated geodesic length, or simply distance.  Diameter  It is the longest path between two specific nodes or actors.  Isolated Actors  Actors that have no link or relation with any other actor in the network. They may also be called disconnected actors.  Connectivity of a Graph  A graph is said to be connected if there exists a path between each pair of nodes; if not, the graph is said to be disconnected.  Components  This name is given to each one of the subgraphs or subgroups that make up a network.  Bridge  It is a critical element in the connectivity of a graph. If, by eliminating a specific link between two actors, the graph becomes disconnected, or else  increases its number of components, that link is known as a bridge of the network.  Cutoff Point  A node or actor is considered to be the cutoff if, by eliminating that node, and therefore its links as well, the graph is left disconnected.

Adjacent Actors. Actors that can be found in direct relation or connection via a link. Neighborhood. Set of actors with which a given actor or node is adjacent. Path. This is the sequence of links and actors that connect two non-adjacent actors, without repeating any of them.  Actor  In a social network graph, the actor may also be referred to as the node, vertex, or point. The actor does not necessarily  have to represent a concrete unit or individual; it may also be a company, institution, or social group.  Link  This may also be called a connection or line, and it may be directional or non-directional, depending on whether it indicates the orientation – from  one actor to another – or does not. In the first case, the link is called an the latter case it is non-directional or reciprocal. Links may or may not be weighted.  There is a special type of link, the self-link or loop, which is produced when an actor makes reference to itself.  Adjacent Actors  Actors that can be found in direct relation or connection via a link.  Neighborhood  Set of actors with which a given actor or node is adjacent.  Indirect Connections  Those made between non-adjacent nodes, through intermediary actors. They can also be called indirect links.  Path  This is the sequence of links and actors that connect two non-adjacent actors, without repeating any of them. The length of the path is determined  by the number of links.  Geodesic Distance  It is the shortest path between two nodes or actors of the network, and can also be denominated geodesic length, or simply distance.  Diameter  It is the longest path between two specific nodes or actors.  Isolated Actors  Actors that have no link or relation with any other actor in the network. They may also be called disconnected actors.  Connectivity of a Graph  A graph is said to be connected if there exists a path between each pair of nodes; if not, the graph is said to be disconnected.  Components  This name is given to each one of the subgraphs or subgroups that make up a network.  Bridge  It is a critical element in the connectivity of a graph. If, by eliminating a specific link between two actors, the graph becomes disconnected, or else  increases its number of components, that link is known as a bridge of the network.  Cutoff Point  A node or actor is considered to be the cutoff if, by eliminating that node, and therefore its links as well, the graph is left disconnected.

Geodesic Distance. It is the shortest path between two nodes or actors of the network. Diameter. It is on average the shortest path between every two nodes or actors in a network. Isolated Actors. Actors that have no link or relation with any other actor in the network. They may also be called disconnected actors.  Actor  In a social network graph, the actor may also be referred to as the node, vertex, or point. The actor does not necessarily  have to represent a concrete unit or individual; it may also be a company, institution, or social group.  Link  This may also be called a connection or line, and it may be directional or non-directional, depending on whether it indicates the orientation – from  one actor to another – or does not. In the first case, the link is called an the latter case it is non-directional or reciprocal. Links may or may not be weighted.  There is a special type of link, the self-link or loop, which is produced when an actor makes reference to itself.  Adjacent Actors  Actors that can be found in direct relation or connection via a link.  Neighborhood  Set of actors with which a given actor or node is adjacent.  Indirect Connections  Those made between non-adjacent nodes, through intermediary actors. They can also be called indirect links.  Path  This is the sequence of links and actors that connect two non-adjacent actors, without repeating any of them. The length of the path is determined  by the number of links.  Geodesic Distance  It is the shortest path between two nodes or actors of the network, and can also be denominated geodesic length, or simply distance.  Diameter  It is the longest path between two specific nodes or actors.  Isolated Actors  Actors that have no link or relation with any other actor in the network. They may also be called disconnected actors.  Connectivity of a Graph  A graph is said to be connected if there exists a path between each pair of nodes; if not, the graph is said to be disconnected.  Components  This name is given to each one of the subgraphs or subgroups that make up a network.  Bridge  It is a critical element in the connectivity of a graph. If, by eliminating a specific link between two actors, the graph becomes disconnected, or else  increases its number of components, that link is known as a bridge of the network.  Cutoff Point  A node or actor is considered to be the cutoff if, by eliminating that node, and therefore its links as well, the graph is left disconnected.

Components. This name is given to each one of the subgraphs or subgroups that make up a network. Bridge. It is the link that if it is eliminated, the graph becomes disconnected. Cutoff Point. A node or actor is considered to be the cutoff if, by eliminating it, the graph is left disconnected.  Actor  In a social network graph, the actor may also be referred to as the node, vertex, or point. The actor does not necessarily  have to represent a concrete unit or individual; it may also be a company, institution, or social group.  Link  This may also be called a connection or line, and it may be directional or non-directional, depending on whether it indicates the orientation – from  one actor to another – or does not. In the first case, the link is called an the latter case it is non-directional or reciprocal. Links may or may not be weighted.  There is a special type of link, the self-link or loop, which is produced when an actor makes reference to itself.  Adjacent Actors  Actors that can be found in direct relation or connection via a link.  Neighborhood  Set of actors with which a given actor or node is adjacent.  Indirect Connections  Those made between non-adjacent nodes, through intermediary actors. They can also be called indirect links.  Path  This is the sequence of links and actors that connect two non-adjacent actors, without repeating any of them. The length of the path is determined  by the number of links.  Geodesic Distance  It is the shortest path between two nodes or actors of the network, and can also be denominated geodesic length, or simply distance.  Diameter  It is the longest path between two specific nodes or actors.  Isolated Actors  Actors that have no link or relation with any other actor in the network. They may also be called disconnected actors.  Connectivity of a Graph  A graph is said to be connected if there exists a path between each pair of nodes; if not, the graph is said to be disconnected.  Components  This name is given to each one of the subgraphs or subgroups that make up a network.  Bridge  It is a critical element in the connectivity of a graph. If, by eliminating a specific link between two actors, the graph becomes disconnected, or else  increases its number of components, that link is known as a bridge of the network.  Cutoff Point  A node or actor is considered to be the cutoff if, by eliminating that node, and therefore its links as well, the graph is left disconnected.

Current Applications... Scientits networks, scienciometry … Organizations Internet Social Support Discourse Analysis Data-mining...

A “Perfect” Network... “Edges” = undirected lines. Degree: A = 4 B, C, D, y E = 1

Degree... “Arcs”= directed lines. Indegree of A=0 B,C,D,E = 1. Conversely, the outdegree is: A= 4 B, C, D y E = 0

Matrix

Betweeness... The betweeness counts the times that a node occurs in the geodesics of the network (that is, in the shorter paths between each pair of nodes). A=12 A = 0

Betweeness... A= 0 (there is not a path that occurs through it), as D and C. B= 1 E= 1

Closeness... Closeness measures the capacity of a node to reach the rest of the nodes of the network. For computing this measure is necessary to summarize all the geodesics of each node with the rest of nodes of the network. This measure is the farness. If we compute the reciprocal we can obtain the closeness.

Closeness... (ii) For doing this calculations is necesary to convert first the oriented data in reciprocal data: Farness of A = 6 (A  B:1; A  C:2;A  E:1;A  D:2) Farness of B = 7 (B  A:1; B  C:1;B  E:2;B  D:3) Farness of C = 10 (C  B:1; C  A:2;C  E:3;C  D:4) Farness of E= 7 Farness of D= 10 All geodesics = 40 The closeness of A= 40/6= 6,667 or 66,67%. B= 40/7= 5,714 = 57,14% C= 40/10 = 4 = 40%

Centrality...

Clustering...

Present & Future... Evolution of Networks Community Studies …... It is up to us