Prof. Virgilio Almeida Mail
Office hours: by appointment
Prerequisites: basic statistics course.
Download the Syllabus in pdf format

Overview and Goals

In this course, we study cyberspace governance. Cyberspace is a unique combination of physical and virtual properties. The course focuses on logic, economic and social aspects of the cyberspace. Due to the decentralized and multi-stakeholder nature of the digital world, cyberspace governance involves governments, private sector, civil society, and technical communities. The transnational nature of cyberspace requires regulations and practices that can not established only at national level. There are many areas of private and public governance that include different stakeholders in national, regional and global agreements.

A quantitative approach is about using data collected from the cyberspace to make better decisions about public and private policies for internet and cyberspace governance. The principles, norms, rules, and procedures that shape the cyberspace are studied in this course through quantitative analysis of data collected from different sources of the digital world. Ultimately, the students will learn how to use quantitative methods to understand different issues related to digital governance.

The course will introduce students to the core technological principles of the Internet and will discuss the complex relationship between technology and social and economic policies that have impact on cyber security, human rights (e.g., freedom of expression, privacy, ethics, and access) and regulatory framework. Specific aspects of Internet governance will be covered in the course, such as multi-stakeholder models, management of critical resources (e.g., domain names, IP numbers and ICANN), net neutrality, cyber security and cyber sovereignty. Throughout the course, students will discuss the role of governments, civil society and private sector in the several dimensions of the global cyberspace governance process.

The course will also focus on the use of quantitative techniques in the context of experimental analysis of cyberspace phenomena. Topics include scientific methods applied to workload characterization, user behavior, hypothesis testing, statistical analyses of data and interpretation and presentation of experimental results. We will look at several measurement studies and use them as instances of a generic empirical framework to analyze complex problems in the processes of cyberspace governance.

Data-oriented analysis of problems and policies in cyberspace will be illustrated by examining several case studies related to user behavior in platforms such as Facebook, Google, Twitter, Uber, Airbnb, and others. The case studies will help the students to understand the role of social algorithms, programs that rank people, evaluate what persons want and provide customized experiences. Algorithms can potentially lead to harmful outcomes, such as interest-driven polarization of political disputes, filter bubbles, price discrimination by online commerce sites against consumers and even gender and racial discrimination.

In conclusion, the central goal of the course is to present students a combination of knowledge from multiple disciplines in order to allow them to carry out evidence-based analysis of problems and issues related to cyberspace governance.

Course Requirements:

There will not be any examinations given in this course.

Cooperation:

Due to the interdisciplinary nature of the course, students will be expected to work with each other and learn from each others' perspectives and backgrounds.

Grading:

30% class participation, 30% reactions and short writing assignments, 40% final project

Planned Course Sequence

Weeks 1-2-3: Cyberspace and Internet Governance Concepts
  1. The development of Internet, the main principles governing Internet
  2. The Regime Complex for Managing Global Cyber Activities
  3. The Convergence of Social and Technological Networks
  4. Internet governance concepts and models
  5. ICANN and management of domain names
  6. IANA and management of IP addresses, the case of IPv6
Readings
  • Chapters 1, 2, 3, 5, 6 and 7 of DeNardis Book [ref. 1]
  • Articles: 1, 2, 3, 4, 5 and 6.
Week 4: Special issues on cyberspace governance
  1. Network Neutrality
  2. Cyber Security
  3. Cyber Sovereignty
  4. Cyber warfare
Weeks 5-6: Quantitative Techniques
  1. Introduction to Experimental Techniques on computer science
  2. Summarizing Measured Data, Comparing Alternatives
  3. Hypothesis testing, characterization of errors
  4. Workload and user behavior characterization
Weeks 7-8: Case Studies
  1. Impact of domain names: "XXXtortion? Inferring Registration Intent in the .XXX TLD";
  2. Impact of domain names: From .academy to .zone: An Analysis of the New TLD Land Rush";
  3. Media: "Quantifying Media Bias in the Digital World”;
  4. Media Discrimination: "Exposure to ideologically diverse news and opinion on Facebook";
  5. Online privacy: The High-School Profiling Attack: How Online Privacy Laws Can Actually Increase Minors Risk;
  6. Online privacy: the Right to Be Forgotten policy of the European Union;
  7. Online Discrimination: "Measuring Price Discrimination and Steering on E-commerce Web Sites";
  8. Gender Discrimination: Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice, and Discrimination";
  9. Online Manipulation: "Experimental evidence of massive-scale emotional contagion through social networks";
  10. Anonymity: "On the Internet, Nobody Knows You’re a Dog": A Twitter Case Study of Anonymity in Social Networks";
  11. Traffic routing, surveillance, and freedom of expression: "Characterizing and Avoiding Routing Detours Through Surveillance States";
Weeks 9-10-11: Algorithm Governance: Transparency, Accounting, and Auditing
  1. Algorithmic culture and the rise of the social algorithm;
  2. Auditing Algorithms: Research Methods for Detecting Discrimination on Internet Platforms;
  3. Uber algorithms: Peeking Beneath the Hood of Uber";
  4. Friend Grouping Algorithms for Online Social Networks: preference, bias, and implications;
  5. Measuring Personalization of Web Search;
  6. Algorithmic Accountability: Journalistic Investigation of Computational Power Structures;
  7. The Secret of Airbnb’s Pricing Algorithm;
  8. Algorithm Bias and Discrimination.
Weeks 12-13: Project Presentations
Reading List: books and articles

There is no required text for this course. Some books are suggested for specific topics. Most of the reading material will be available on the course website. Outside speakers will also be invited to shed light on some of the topics.

BOOKS
  1. DeNardis Laura,The Global War for Internet Governance, Yale University Press 2014.
  2. Zittrain, John, The Future of the Internet - And How to Stop It. 2008. New Haven, Yale University Press.
  3. P. Cohen, Empirical Methods for Artificial Intelligence, MIT Press, 1995.
  4. Frank Pasquale,The Black Box Society: The Secret Algorithms That Control Money and Information, Harvard University Press, January 2015
  5. Cathy O’Neil,Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, Crown Books, September 6, 2016
  6. Adam Segal, The Hacked World Order: How Nations Fight, Trade, Maneuver, and Manipulate in the Digital Age, Publicaffairs, 2016
ARTICLES: journals and conferences
  1. Nye, Joseph, "The Regime Complex for Managing Global Cyber Activities", Global Commission on Internet Governance Paper Series No. 1, November 2014
  2. Nye, Joseph, ”Cyber Power,“ Belfer Center for Science & International Affairs (May, 2010).
  3. Clark David, Characterizing Cyberspace: Past, Present, and Future, ECIR Working Paper, Version 1.2, March 12, 2010
  4. Kleinberg J., "The Convergence of Social and Technological Networks, Communications of the ACM, Vol. 51 No. 11, Pages 66-72
  5. Almeida, V, Getschko D., and Afonso C., “The Origin and Evolution of Multistakeholder Models,” IEEE Internet Computing, vol. 19, no. 1, 2015, pp. 65–69.
  6. Doneda D. and Almeida V., Privacy Governance in Cyberspace", IEEE Internet Computing 19(3): 50-53 (2015]
  7. Kleinwächter W., Almeida V.,"The Internet Governance Ecosystem and the Rainforest", IEEE Internet Computing 19(2): 64-67 (2015)
  8. Le Chen, Alan Mislove, and Christo Wilson,"Peeking Beneath the Hood of Uber", ACM Internet Measurement Conference (IMC), 2015
  9. S.T. Peddinti, K.W. Ross, J. Cappos,On the Internet, Nobody Knows You’re a Dog: A Twitter Case Study of Anonymity in Social Networks, ACM Conference on Online Social Networks (COSN), 2014
  10. R. Dey, Y. Ding, K.W. Ross, The High-School Profiling Attack: How Online Privacy Laws Can Actually Increase Minors Risk, ACM Internet Measurement Conference (IMC), 2013
  11. Halvorson, Der, Foster, Savage, Saul and Voelker, From academy to .zone: An Analysis of the New TLD Land Rush, ACM Internet Measurement Conference (IMC), 2015
  12. Liu, Foster, Savage, Voelker and Saul. Who is .com? Learning to Parse WHOIS Records, ACM Internet Measurement Conference (IMC), 2015
  13. Steven Englehardt, Christian Eubank, Peter Zimmerman, Dillon Reisman, Arvind Narayanan, Web privacy measurement: Scientific principles, engineering platform, and new results
  14. Alvorson, Levchenko, Savage and Voelker "XXXtortion? Inferring Registration Intent in the .XXX TLD", ACM World Wide Web Conference 2014.
  15. Y. Lin, J. Bagrow, and D. Lazer, “More Voices than Ever? Quantifying Media Bias in Networks,” ICWSM-11, Barcelona, 2011.
  16. D. Lazer, A. Pentland, L. Adamic, S. Aral, A-L Barabasi, D. Brewer, N. Christakis, N. Contractor, J. Fowler, M. Gutmann, T. Jebara, G. King, M. Macy, D. Roy, and M. Van Alstyne “Computational Social Science,” Science, February 6, 2009.
  17. D. Lazer, The rise of the social algorithm, Science, 5 June 2015: 348 (6239), 1090-1091
  18. Zhi Yang, Christo Wilson, Xiao Wang, Tingting Gao, Ben Y. Zhao and Yafei Dai, "Uncovering Social Network Sybils in the Wild", ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 8, No. 1, February 2014.
  19. Gasser Urs, et al., Internet Monitor 2014: Reflections on the Digital World: Platforms, Policy, Privacy, and Public, Berkman Center Research Publication No. 2014-7
  20. Savage, S., Monroy-Hernández, A. (2015) Participatory Militias: An Analysis of an Armed Movement's Online Audience. In Proceedings of the ACM Conference on Computer Supported Collaborative Work (CSCW '15).
  21. De Choudhury, M., Monroy-Hernández, A., Mark, G. (2014) "Narco" Emotions: Affect and Desensitization in Social Media during the Mexican Drug War. In Proceedings the ACM Conference on Human Factors in Computing Systems (CHI '14)
  22. Diego Couto de Las Casas, Gabriel Magno, Evandro Cunha, Marcos André Gonçalves, César Cambraia, Virgilio Almeida, "Noticing the other gender on Google+", ACM WebSci 2014: 156-16
  23. Raphael Ottoni, João Paulo Pesce, Diego B. Las Casas, Geraldo Franciscani Jr., Wagner Meira Jr., Ponnurangam Kumaraguru, Virgilio Almeida, "Ladies First: Analyzing Gender Roles and Behaviors in Pinterest, Proceedings of ICWSM 2013.
  24. Solomon Messing, Eytan Bakshy, and Lada A. Adamic , "Exposure to ideologically diverse news and opinion on Facebook", Science 5 June 2015: 1130-1132.
  25. Amit Datta, Michael Carl Tschantz, Anupam Datta, Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice, and Discrimination, in Proceedings on Privacy Enhancing Technologies. Volume 2015, Issue 1, Pages 92–112.
  26. Aniko Hannak, Gary Soeller, David Lazer, Alan Mislove, and Christo Wilson, "Measuring Price Discrimination and Steering on E-commerce Web Sites" Proceedings of Internet Measurement Conference (IMC 2014).
  27. Aniko Hannak, Piotr Sapiezynski, Arash Molavi Kakhki, Balachander Krishnamurthy, David Lazer, Alan Mislove, and Christo Wilson, "Measuring Personalization of Web Search", Proceedings of the 22nd International World Wide Web Conference (WWW 2013)
  28. Adam D. I. Kramer, Jamie E. Guillory, and Jeffrey T. Hancock,Experimental evidence of massive-scale emotional contagion through social networks, PNAS 2014 111: 8788-8790.
  29. C. Sandvig, K. Hamilton, K. Karahalios, and C. Langbort. Auditing Algorithms: Research Methods for Detecting Discrimination on Internet Platforms, ICA 2014
  30. M. Eslami, A. Aleyasen, R. Zilouchian Moghaddam, and K. Karahalios.Friend Grouping Algorithms for Online Social Networks: preference, bias, and implications. Social Informatics (SocInfo), 2014.
  31. Ted Striphas, "Algorithmic Culture", European Journal of Cultural Studies, 2015, Vol. 18(4-5) 395–412
  32. Diakopoulos, Nicholas. “Algorithmic Accountability: Journalistic Investigation of Computational Power Structures," Digital Journalism, 2015,
  33. Hill, D., The Secret of Airbnb’s Pricing Algorithm, IEEE Spectrum August 2015.
  34. S.T. Peddinti, K.W. Ross, J. Cappos, "On the Internet, Nobody Knows You’re a Dog": A Twitter Case Study of Anonymity in Social Networks, ACM Conference on Online Social Networks (COSN), 2014
  35. Giovanni Comarela, Mark Crovella, Virgílio Almeida and Fabrício Benevenuto (2012)."Understanding Factors that Affect Response Rates in Twitter", In: Proceedings of ACM Hypertext. Milwaukee, WI
  36. Latanya Sweeney, "Discrimination in Online Ad Delivery", Communications of the ACM, Vol. 56 No. 5, Pages 44-54
  37. Jon Penney, Chilling Effects: Online Surveillance and Wikipedia Use, Berkeley Technology Law Journal, 2016
  38. Minhui Xue, Gabriel Magno, Evandro Cunha, Virgilio Almeida, Keith W Ross, The Right to be Forgotten in the Media: A Data-Driven Study, Proceedings on Privacy Enhancing Technologies, No. 4, 2016.
  39. Anne Edmundson, Roya ENsafi, Nick Feamster, Jennifer Rexford,Characterizing and Avoiding Routing Detours Through Surveillance States, May 2016.
  40. Samantha Bradshaw and Laura DeNardis, The politicization of the Internet’s Domain Name System: Implications for Internet security, universality, and freedom, New Media & Society, SAGE Publications, 2016
  41. W Kuan Hon et al., Policy, Legal and Regulatory Implications of a Europe-Only Cloud, Queen Mary University of London, School of Law, Legal Studies Research Paper 191/2015
  42. Arnbak Axel and Goldberg Sharon, Loopholes for Circumventing the Constitution: Unrestrained Bulk Surveillance on Americans by Collecting Network Traffic Abroad, Michigan Telecommunications and Technology Law Review, Volume 21, Issue 2, 2015.
  43. Bonnefon, Jean-François et al. "The social dilemma of autonomous vehicles, Science 24 Jun 2016: Vol. 352, Issue 6293, pp. 1573-1576
  1. Lecture 1
  2. Lecture 2
  3. Lecture 2b
  4. Lecture 2c
  5. Lecture 2d
  6. Lecture 2f
  7. Lecture 2g
  8. Lecture 3a
  9. Lecture 3b
  10. Lecture 3c
  11. Lecture 3d
  12. Lecture 3e
  13. Lecture 4a
  14. Lecture 4b
  15. Lecture 4c
  16. Lecture 4d
  17. Lecture 5a
  18. Lecture 5b
Additional References
  1. Reference[6]
  2. Reference about social media governance
  3. iphone security issues
  4. Unique-crowd
  5. Unique-shopping
  6. IoT-governance
  7. Going Dark: Who is our enemy?
  8. Slides Prof PK's talk
  9. IoT-concepts
  10. IoT-security
  11. IoT-governance
  12. Report-template