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Network Construction and Visualization.pdf
This document is a slide presentation about network construction and visualization. It begins with an introduction and overview of the speaker's background and interests related to data, information, and knowledge. It then provides timelines of the internet and social media. The presentation discusses the explosion of big data and digitization projects, and provides examples of network visualization tools and datasets. It introduces basic concepts in network analysis including graph representations, metrics, and identifying key nodes. The presentation concludes with examples of different types of networks and how network properties can evolve over time.
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Network Construction and Visualization.pdf
- 1. Network construction and visualization FranciscoRestivo frestivo@ucp.pt slideshare.net/frestivo favinks.com/board/FranciscoRestivo
- 2. Thank you • I appreciatevery much the invitation and your presence • I enjoy these dialogues • Ask, interrupt, don't let doubts persist • And don't forget, the teacher always learns... 2 Escola das Artes 2023
- 3. Advance notice • My fieldis Informatics, that is, Automatic Information • Basically, it's about teaching machines to solve problems • I'm interested in problems related to – Data → Information → Knowledge • Think of me as a translator... 3 Escola das Artes 2023
- 4. About me 4 Escola dasArtes 2023 Lic. EE (6 anos) D.Phil. Prof. Assoc. Director Prof. Assoc Signals DSP Multiprocessor systems Biomedical Systems Complex systems Manufacturing systems Multi-agent systems Social systems Networks Lic. EE (6 anos) D.Phil. Prof. Assoc. Director Prof. Assoc Lic. EE (6 anos) D.Phil. Prof. Assoc. Director Prof. Assoc. 1970
- 5. Internet timeline 5 Escola dasArtes 2023
- 6. IBM PC 1981 6 Escoladas Artes 2023
- 7. Social media timeline 7 Escoladas Artes 2023 htps://www.broadbandsearch.net/ 7 7
- 8. Where are we? • Theexplosion of Big Data • Networks everywhere • Social Networks • Technologies • Tools • Projects • Digitization 8 Escola das Artes 2023
- 9. 9 Escola das Artes2023 An Internet minute
- 10. And heritage? • Documents • Pictures, etc • Digitized? • Aquick tour 10 Escola das Artes 2023
- 11. A quick tour • Someprojects • Basic ideas • How does a 'data scientist' think? • Collaborative platforms • Digital Humanities 11 Escola das Artes 2023
- 12. 12 Escola das Artes2023 slideshare.net/frestvo
- 13. 13 Escola das Artes2023 htp://www.martngrandjean.ch/
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- 16. 16 Escola das Artes2023 htps://www.familysearch.org/
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- 21. Challenges and opportunities • Existingdata and changing management • Data discovery, access and reuse • Digital skills • There is an enormous potential in the network approach 21 Escola das Artes 2023
- 22. Data science approach • Regularities • Correlations • Causality • Relations/networks/distances/clusters • Co-occurrences • Deeplearning, etc 22 Escola das Artes 2023
- 23. The plan fortoday • A realistic plan – Part 1: some work hands on with real data – Part 2: very basic ideas on data structures and networks • Please feel free to question, interrupt, etc 23 Escola das Artes 2023
- 24. Escola das Artes2023 24 Questions?
- 25. Part 1 25 Escola dasArtes 2023
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- 27. Where to obtain? • Makeor get! • Usually, we know our subject • There are many sites you can visit – kaggle – data.world 27 Escola das Artes 2023
- 28. Co-authors, in aDepartment 28 Escola das Artes 2023
- 29. APIs • Application Programming Interfaces • Allmajor platforms offer APIs – ChatGPT offers an API • Python is friendly Escola das Artes 2023 29
- 30. Escola das Artes2023 30 polsys.net
- 31. Coldplay musical universe 31 Escoladas Artes 2023
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- 36. 36 Escola das Artes2023 dimensions.ai
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- 42. Characters, Les Misérables 42 Escoladas Artes 2023
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- 46. 46 Escola das Artes2023 nocodefunctons.com
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- 54. Escola das Artes2023 54 Questions?
- 55. Part 2 55 Escola dasArtes 2023
- 56. Computer programs • Algorithms +Data Structures • Many programming language (your choice) • Programming is a communication task – Shared concepts – Well defined actions 56 Escola das Artes 2023
- 57. Data structures • Lists • Stacks • Queues • Linked lists • Trees • Graphs –Objects + attributes + relations 57 Escola das Artes 2023
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- 59. Graph database 59 Escola dasArtes 2023 htps://neo4j.com/
- 60. Algorithms • Sort • Search • Insert/delete • Data analysis, datamining, etc • Graph algorithms 60 Escola das Artes 2023
- 61. Networks • Social, biological, financial,etc • Complex networks • Communities • Contagion • Controversies • Society! 61 Escola das Artes 2023
- 62. Social interactions • Like, comment,share, cite • Dating • e-Commerce • Payments • Digital marketing • Political marketing • Crime 62 Escola das Artes 2023
- 63. Metaverse? • Virtual • Augmented • Fake • Holograms • New, or more ofthe same? 63 Escola das Artes 2023
- 64. SO?! Escola das Artes2023 64 • Let's have a look at networks and graphs
- 65. Euler 1707 -1783 Escola das Artes 2023 65
- 66. Actors and interactions • Networksare made of actors and interactions • Actors from one or more sets – People and movies, eg • Interactions of one or more types – Follow and retweet, eg • Actors and interactions may have other atributes Escola das Artes 2023 66
- 67. Basics of graphsand networks • G = (V, E) vertices and edges • O(G) = |V| order • S(G) = |E| size • A adjacency matrix • Ki degree of vertex i • Directed/undirected Escola das Artes 2023 67
- 68. ● Directed/undirected? ● Usually not transitive –a likes b and b likes c does not imply a likes c ● Directed > Order (total/partial) – Rankings, proeminence indexes, etc ● Undirected > Equivalence – Communities, clusters, etc Escola das Artes 2023 68 Network edges
- 69. Representations of networks • Matrixes,graphs, edge lists, etc A B A C A D B A B C B E C D D B D C E A E B Escola das Artes 2023 69 A B C D E A 0 1 1 1 0 B 1 0 1 0 1 C 0 0 0 1 0 D 0 1 1 0 0 E 1 1 0 0 0
- 70. Global metrics • Number ofvertices 5 • Number of edges 11 • Number of components 1 • Diameter 2 • Density 0.55 Escola das Artes 2023 70
- 71. Centrality Measures • Degree centrality –Edges per node • Closeness centrality – How close the node is to every other node • Betweenness centrality – How many shortest paths go through the node • Bibliometric + Internet style (quality of edges) – PageRank, eigenvector 71 Escola das Artes 2023
- 72. Which metrics? • Depend ofthe answers we need – Key nodes – Ranking – Influence, contagion – Communities, etc • That's what network science is all about • You have to know the problem 72 Escola das Artes 2023
- 73. Which networks? • Identifying networksmay be not intuitive • But at the end is all about actors and interactions – Vertices = nodes = actors – Edges = relations = interactions • Going through examples is helpful 73 Escola das Artes 2023
- 74. My FB, LostCircles 74 Escola das Artes 2023
- 75. Countries, FIFA WorldCup 75 Escola das Artes 2023
- 76. New Testament 76 Escola dasArtes 2023
- 77. Reccomendation systems • Bipartite networks:two types of nodes • Two similarity networks Escola das Artes 2023 77
- 78. Bipartite networks Escola dasArtes 2023 78
- 79. Dynamics • Networks may havea temporal dimension • Interactions – follow, like, share, mention, retweet, hashtag, etc – occur in sequence • Network properties evolve in time Escola das Artes 2023 79
- 80. Thank you! Escola dasArtes 2023 80