Introduction to Network Analysis saverio . giallorenzo @gmail.com 1 - PowerPoint PPT Presentation

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Introduction to Network Analysis saverio . giallorenzo @gmail.com � 1

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks, examples saverio . giallorenzo @gmail.com � 2

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks saverio . giallorenzo @gmail.com � 3

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks, examples They hate each other Romeo’s father Juliet’s father Juliet’s cousin They love each other They planned a ruse Romeo’s best friend Juliet best friend saverio . giallorenzo @gmail.com � 4

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks A network is a simplified representation that reduces a system to an abstract structure or topology , capturing only the basics of the connection patterns and little else. saverio . giallorenzo @gmail.com � 5

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks • Networks capture the pattern of interactions between the parts of a system. In turn, the pattern of interactions have a sensible e ff ect on the behaviour of a system. • Examples: • the pattern of connections between computers on the Internet a ff ects the routes that data take over the network and hence the e ffi ciency with which the network transports those data. • the connections in a friendship network a ff ect how people learn, form opinions, and gather news, as well as other less obvious phenomena, such as the spread of disease. • Knowing the structure of a network is essential to fully understand how its corresponding system works. saverio . giallorenzo @gmail.com � 6

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks The systems studied can have interesting features not represented by the network—e.g., the detailed behaviours of individual nodes, such as people and the precise nature of the interactions between them. saverio . giallorenzo @gmail.com � 8

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Mercutio Tybalt Networks, examples Prince Paris Romeo Juliet Benvolio Friar The Laurence Nurse Apothecary Friar John Lady Lady Capulet Montague Lord Lord Capulet Montague saverio . giallorenzo @gmail.com � 9

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks We can capture additional information by labelling the nodes and/or edges of the network, such as with names or strengths of interactions. saverio . giallorenzo @gmail.com � 10

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo kills Mercutio Tybalt Networks, examples Prince Paris friendship cousin in love Romeo Juliet friendship servant/friend in cahoots Benvolio Friar The Laurence dealership Nurse lost Apothecary Friar John Lady Lady Capulet o ff spring o ff spring Montague married married Lord Lord in feud Capulet Montague saverio . giallorenzo @gmail.com � 11

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks Finding what is the “right” kind/amount of information to make a system treatable (to reasoning) is a work of craftsmanship and experience. The invariant here is that, every time we define a representation of a full system, we decide to filter out some information. saverio . giallorenzo @gmail.com � 12

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo ♠ Mercutio Tybalt Networks, examples Prince Paris ❤ ❤ ❤ Romeo Juliet ❤ ❤ ❤ ❤ Benvolio Friar The Laurence ♣ Nurse ♣ Apothecary Friar John Lady Lady Capulet ❤ ❤ Montague ❤ ❤ Lord ♠ Lord Capulet Montague saverio . giallorenzo @gmail.com � 13

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo kills Networks, examples friendship cousin in love Juliet friendship servant/friend in cahoots dealership lost o ff spring o ff spring married married in feud saverio . giallorenzo @gmail.com � 14

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks, examples The Internet map saverio . giallorenzo @gmail.com � 21

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks, examples Russia United Kingdom Ukraine Poland U.S.A Italy Germany France Spain India Cina Iran Japan Brazil saverio . giallorenzo @gmail.com � 22

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Network Analysis The founding questions behind network analysis are: • If we know the shape of a network, what can we learn about the nature and function of the system it describes? • How are the structural features of a network related to the practical issues we care about? saverio . giallorenzo @gmail.com � 23

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Network Analysis A first step in analysing the structure of a network is often to make a picture of it. Automatic tools help in managing, visualising, and exploring networks. Visualisation is a useful tool in the analysis of network data, allowing us to instantly see important structural features that would otherwise be di ffi cult to pick out of the raw data. The human eye is enormously gifted at discerning patterns , and visualisations allow us to put this gift to work on our network problems. saverio . giallorenzo @gmail.com � 24

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Network Analysis While we are good at spotting patterns, we can feasibly do that manually up to a few hundreds or thousands of nodes and for networks that are relatively sparse—whose number of edges is quite small. To address these issues, network theory has developed a large tool-chest of measures and metrics that “mimic” some specific abilities of our eyes, to help us when visualisation is impossible or unreliable. saverio . giallorenzo @gmail.com � 26

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Network Analysis • An example of a useful (and widely used) class of network measures are the centrality measures . • Centrality quantifies how important nodes are in a network . • While the concept is clear, what it (mathematically) means for a node to be central in a network may vary. • The simplest centrality measure is called degree . The degree of a node in a network is the number of edges attached to it. • In many cases, the nodes with the highest degrees in a network also play major roles in the functioning of the system. Hence the node’s degree can be a useful guide to focus our attention on a system’s most important elements. saverio . giallorenzo @gmail.com � 27

Web Science • Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Networks, examples Google Yahoo Twitter Ask.com Microsoft Facebook saverio . giallorenzo @gmail.com � 28

Introduction to Network Analysis saverio . giallorenzo @gmail.com 1 - PowerPoint PPT Presentation

Web Science Introduction to Network Analysis MA Digital Humanities and Digital Knowledge, UniBo Introduction to Network Analysis saverio . giallorenzo @gmail.com 1 Web Science Introduction to Network Analysis MA Digital Humanities and

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