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<html> <!– Google Analytics –> <script type=“text/javascript” charset=“utf-8”> (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) })(window,document,'script','www.google-analytics.com/analytics.js','ga'); ga('create', 'UA-34685760-1', 'auto', 'personalTracker', {'allowLinker': true}); ga('personalTracker.require', 'linker'); ga('personalTracker.linker:autoLink', ['pages.di.unipi.it', 'enforce.di.unipi.it', 'didawiki.di.unipi.it'] ); ga('personalTracker.require', 'displayfeatures'); ga('personalTracker.send', 'pageview', 'ruggieri/teaching/sna/'); setTimeout(“ga('send','event','adjusted bounce rate','30 seconds')”,30000); </script> <!– End Google Analytics –> <!– Global site tag (gtag.js) - Google Analytics –> <script async src=“https://www.googletagmanager.com/gtag/js?id=G-LPWY0VLB5W”></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-LPWY0VLB5W'); </script> <!– Capture clicks –> <script> jQuery(document).ready(function(){ jQuery('a[href$=“.pdf”]').click(function() { var fname = this.href.split('/').pop(); ga('personalTracker.send', 'event', 'SNA', 'PDFs', fname); }); jQuery('a[href$=“.r”]').click(function() { var fname = this.href.split('/').pop(); ga('personalTracker.send', 'event', 'SNA', 'Rs', fname); }); jQuery('a[href$=“.zip”]').click(function() { var fname = this.href.split('/').pop(); ga('personalTracker.send', 'event', 'SNA', 'ZIPs', fname); }); jQuery('a[href$=“.mp4”]').click(function() { var fname = this.href.split('/').pop(); ga('personalTracker.send', 'event', 'SNA', 'Videos', fname); }); jQuery('a[href$=“.flv”]').click(function() { var fname = this.href.split('/').pop(); ga('personalTracker.send', 'event', 'SNA', 'Videos', fname); }); }); </script> </html> ====== Social Network Analysis ====== * Dino Pedreschi Università di Pisa, Knowledge Discovery and Data Mining Lab pedre [at] di [dot] unipi [dot] it * Teaching assistants: Luca Pappalardo lpappalardo [at] di [dot] unipi [dot] it and Giulio Rossetti giulio [dot] rossetti [at] isti [dot] cnr [dot] it, Knowledge Discovery and Data Mining Lab ===== News ===== * Next exam session: September 2nd 2015, h 9:00, Pedreschi's office * Giovedì 4 June, h 11:00-13:00, Aula Seminari Ovest del Dipartimento di Informatica: Seminars of PhD students Ioanna Miliou (link prediction/social influence) and Farzad Vaziri (mobility data mining). * Exams are on appointment with the instructors. Reference dates for setting the exam calendar are: 12 June, 30 June, and 20 July. Each group is expected to contact instructors by email 3 days before the above dates, communicating their intention to discuss the exam and delivering the project report. * Venerdi 10 aprile alle 17, presso la Libreria Blu Book di Palazzo Blu in Via Toselli 23 a Pisa, si tiene la presentazione del volume “Homo Pluralis. Essere umani nell'era tecnologica” di Luca De Biase.link * First lecture: Monday, Feb. 23, 2015 - h 16:00-18:00 - Aula B ===== 2015 Schedule ===== * Monday, h 16:00 - 18:00, Aula B * Thursday, h 11:00 - 13:00, Aula N1 ====== Goals ====== Over the past decade there has been a growing public fascination with the complex “connectedness” of modern society. This connectedness is found in many contexts: in the rapid growth of the Internet and the Web, in the ease with which global communication now takes place, and in the ability of news and information as well as epidemics and financial crises to spread around the world with surprising speed and intensity. These are phenomena that involve networks and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which each of our decisions can have subtle consequences for the outcomes of everyone else. This short course is an introduction to the analysis of complex networks, with a special focus on social networks and the Web - its structure and function, and how it can be exploited to search for information. Drawing on ideas from computing and information science, applied mathematics, economics and sociology, the course describes the emerging field of study that is growing at the interface of all these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected. ====== Syllabus ====== 1) Graph theory and social networks * Graphs * Social, information, biological and technological networks * Strong and weak ties * Networks in their surrounding context 2) The World Wide Web * The structure of the Web * Link analysis and Web search * Web mining e sponsored search markets 3) Network dynamics * Information cascades * Power laws and rich-get-richer phenomena * The small-world phenomenon * Epidemics ====== Textbooks and materials ====== * Slides (see Calendar). * David Easley, Jon Kleinberg: Networks, Crowds, and Markets. http://www.cs.cornell.edu/home/kleinber/networks-book/ * Albert-Laszlo Barabasi. Network Science Book Project (2013, ongoing) http://barabasi.com/book/network-science Reading: * M. E. J. Newman: The structure and function of complex networks, SIAM Review, Vol. 45, p. 167-256, 2003. (download pdf) * A.-L. Barabasi. Linked. PLUME, Penguin Group, 2002. * Duncan J. Watts. Six Degrees: The Science of a Connected Age. Norton, New York, 2003. * Anand Rajaraman, Jeffrey D. Ullman, Mining of Massive Datasets. http://infolab.stanford.edu/~ullman/pub/book.pdf Course on Network Science held by Albert-Laszlo Barabasi at Northeastern University, Boston, MA: link ===== MidTerm Project ===== * Assignment: Mid Term 2015 * Results: Mid Term results Software: * Visual Analytics: Cytoscape, Gephi * Python 2.7: Guide and Download, PyCharm, NetworkX Data Collection: * Lastfm, Echonest * Python Script ====== Final Project ====== * Assignment: Final Project * SIR-SIS python library: NepidemiX ====== Calendar ====== ^ ^ Date ^ Topic ^ Learning material ^ Homework ^ |1. | Monday, 23.02.2015 | Introduction to Complex Network Analysis. | slides | Reading: Chapter 1, 2 of Kleinberg's book and Chapter 1 of Barabasi's book. | |2. | Monday, 02.03.2015 | Basic network measures: degree, distance, clustering | | Reading: Chapter 1, 2 of Barabasi's book. | |3. | Thursday, 05.03.2015 | Basic network measures: degree, distance, clustering | slides | | |4. | Monday, 09.03.2015 | Random graphs and real networks | slides Random Networks - Barabasi | Reading: Chapter 3 of Barabasi's book | |5. | Thursday, 12.03.2015 | Random graphs and real networks | Random Networks - Barabasi | | |6. | Monday, 16.03.2015 | Scale free networks | Scale free networks - Barabasi | Reading: Chapter 4 of Barabasi's book | |7. | Thursday, 19.03.2015 | Scale free networks |slides | |8. | Monday, 23.03.2015 | Small world, Strength of weak ties | slides | Reading: Chapter 3 of Kleinberg's book, Milgram's small world experiment, Watts' email experiment, Leskovec's IM experiment, Granovetter's Strength of Weak Ties theory, Onnela et al.'s Strength of Weak Ties experiment | |9. | Thursday, 26.03.2015 | Centrality measures |slides | |10. | Monday, 30.03.2015 | Network analytics tools (Cytoscape, Gephi, NetworkX) | | Guest lecturer: Giulio Rossetti | |11. | Monday, 20.04.2015 | Network models: Small World model and Barabasi-Albert model (Preferential attachment) | slides Small World Model slides Barabasi Albert Model | Read Chapters 4 and 5 of Barabasi's book. Read original papers of Watts-Strogatz model and Barabasi-Albert model | |12. | Thursday, 23.04.2015 | Network robustness to failures and attacks | | Reading: Chapter 8 of Barabasi's book | |13. | Monday, 27.04.2015 | Community discovery | slides | Guest lecturer: Giulio Rossetti | |14. | Thursday, 30.04.2015 | Link prediction | | Guest lecturer: Luca Pappalardo | |15. | Monday, 04.05.2015 | Student Q&A for Mid Term Project | | |16. | Thursday, 07.05.2015 | Diffusion, Spreading & Epidemics: introduction | slides | Reading: Chapter 16 of Kleinberg's book | | | Monday, 11.05.2015 | BI Seminar: Marketing plan in 7 steps | | Lecturer: Maurizio Fionda (Aula Seminari Est) | |17. | Thursday, 14.05.2015 | Diffusion, Spreading & Epidemics: Decision Models | slides | Reading: Chapter 19 of Kleinberg's book. Bryce Ryan and Neal C. Gross. The diffusion of hybrid seed corn in two Iowa communities | |18. | Monday, 18.05.2015 | Diffusion, Spreading & Epidemics: Decision Models | | Lezione cancellata per motivi di salute del docente | |19. | Thursday, 21.05.2015 | Diffusion, Spreading & Epidemics: SIS, SIR models and networks | | |20. | Monday, 25.05.2015 | Network effects: Schelling's segregation model | | |21. | Thursday, 28.05.2015 | Student Q&A for Final Project. PhD students presentations | | ====== Link alle edizioni precedenti ====== * Social network analytics, Data science ethics & privacy-preserving analytics at ACM Summer School 2017 Social Network Analytics, Data Ethics & Privacy-preserving Analytics * Janos Kertesz - Introduction to Network Science at PhD Unipi 2017 JanosKertesz2017 * Social Network Analysis crash course at Universitat Pompeu Fabra Barcelona Social Network Analysis - Crash Course at Universitat Pompeu Fabra - Barcelona - May 2016 * Edizione 2013-2014 Web Mining and Social Network Analysis 2014 * Edizione 2012-2013 Web Mining and Social Network Analysis 2012/2013 * Edizione 2011-2012 Web Mining and Social Network Analysis 2011-2012 * Edizione 2010-2011 Web Mining ed Analisi delle Reti Sociali 2010 - 2011 * Edizione 2008-2009 Web Mining ed Analisi delle Reti Sociali 2008-2009