School of Information and Library Science
University of North Carolina, Chapel Hill
INLS 490-141 – Datafication of Everything
[Last Updated: 2018-01-31]

Spring 2018
Meeting Time: Wednesday, 9:05-11:25
Location: Manning 117
Credits: 3
Instructor: Cal Lee
Office: Manning 212
Phone: 919-962-7024
E-Mail: callee [at][ils - DOT - unc DOT - edu]
Office Hours: Wednesday, 11:30-12:30, or by appointment
Course Web Site: http://sakai.unc.edu/

COURSE DESCRIPTION

Whether it's in-store shopping, online commerce, transportation, health care, fitness, law enforcement, entertainment or informal social interaction, our activities are increasingly "datafied."  Processes and events leave digital traces, which can potentially be retained, combined, transformed and accessed by a variety of agents (human and machine).  Digital traces take many different forms and levels of representation; and those forms/levels significantly shape what one can understand or infer.   In this course, we will explore the datafication of various arenas of activity, the nature of the digital data involved, and the implications for information professionals.

COURSE OBJECTIVES

Upon completion of this course, you should be able to:

COURSE EXPECTATIONS

Special Needs: If you feel that you may need an accommodation for a disability or have any other special need, please make an appointment to discuss this with me. I will best be able to address special circumstances if I know about them early in the semester. My office hours and contact information are listed at the beginning of this syllabus.

Diversity Statement
"In support of the University’s diversity goals and the mission of the School of Information and Library Science, SILS embraces diversity as an ethical and societal value. We broadly define diversity to include race, gender, national origin, ethnicity, religion, social class, age, sexual orientation and physical and learning ability. As an academic community committed to preparing our graduates to be leaders in an increasingly multicultural and global society we strive to:

The statement represents a commitment of resources to the development and maintenance of an academic environment that is open, representative, reflective and committed to the concepts of equity and fairness."

~The faculty of the School of Information and Library Science (http://sils.unc.edu/about/diversity)

COURSE REQUIREMENTS

  1. Complete required readings and participate in class discussions (in person and online).
  2. Article of the week - For one week of class (assigned to you based on your expressed interests), identify an additional article (published since 2015) that is on the topic of the week, and post a summary and set of discussion questions to Sakai by 11pm on the Sunday before class.  For at least five weeks, contribute to the discussion about one or more of the articles of the week by 5pm on the Tuesday before class
  3. Submit a proposed final paper topic to Sakai by 5pm on Friday, January 26.
  4. Share a full draft of your final paper to a peer review partner by 9am on Wednesday, April 4.
  5. Provide feedback to your peer review partner by 9am on Wednesday, April 11.  Discuss the paper with your partner in class on April 11.
  6. Submit final paper to Sakai by 9am on Wednesday, April 18.  Your paper should be 10-15 pages (double spaced), addressing the implications of datafication in a specific contemporary context.
  7. Give final paper presentation in class on Wednesday, April 25.

IMPORTANT NOTE ON PLAGIARISM

It is very important that you both attribute your sources and avoid excessive use of quotes (see separate document called "In Your Own Words"). Be aware of the University of North Carolina policy on plagiarism. Your written work must be original. Ask if you have any doubts about what this means.

All cases of plagiarism (unattributed quotation or paraphrasing) of anyone else's work, whether from someone else's answers to homework or from published materials, will be officially reported and dealt with according to UNC policies (Instrument of Student Judicial Governance, Section II.B.1. and III.D.2, http://instrument.unc.edu).

EVALUATION

Participation in class discussions and exercises: 30%

Article of the Week: 10%

Peer Feedback on Draft of Final Paper: 10%

Final Paper: 40%

Presentation on Final Paper: 10%

The most important measures of your performance in this and all other classes at SILS will be your ability to engage in challenging materials with your fellow students; your reputation for insights and professionalism among your peers and with your instructor; your integration of course material with the other things you are learning both inside and outside the classroom; and your ability to apply what you’ve learned in your future career. However, the conventions of academia dictate that I also assign labels (called grades) to your work on assignments and for the course as a whole.

Based on UNC Registrar Policy for graduate-level courses (http://registrar.unc.edu/academic-services/grades/explanation-of-grading-system/), both assignment and semester grades will be H, P, L or F. Few students will obtain an "H," which signifies an exceptionally high level of performance (higher than an "A" in an A-F systems). The following is a more detailed breakdown:

H Superior work: complete command of subject, unusual depth, great creativity or originality
P+ Above average performance: solid work somewhat beyond what was required and good command of the material
P Satisfactory performance that meets course requirements (expected to be the median grade of all students in the course)
P- Acceptable work in need of improvement
L Unacceptable graduate performance: substandard in significant ways
F Performance that is seriously deficient and unworthy of graduate credit

According to UNC Registrar Policy, undergraduate grades are based on the following definitions:

A Mastery of course content at the highest level of attainment that can reasonably be expected of students at a given stage of development. The A grade states clearly that the students have shown such outstanding promise in the aspect of the discipline under study that he/she may be strongly encouraged to continue.
B Strong performance demonstrating a high level of attainment for a student at a given stage of development. The B grade states that the student has shown solid promise in the aspect of the discipline under study.
C A totally acceptable performance demonstrating an adequate level of attainment for a student at a given stage of development. The C grade states that, while not yet showing unusual promise, the student may continue to study in the discipline with reasonable hope of intellectual development.
D A marginal performance in the required exercises demonstrating a minimal passing level of attainment. A student has given no evidence of prospective growth in the discipline; an accumulation of D grades should be taken to mean that the student would be well advised not to continue in the academic field.
F For whatever reason, an unacceptable performance. The F grade indicates that the student's performance in the required exercises has revealed almost no understanding of the course content. A grade of F should warrant an advisor's questioning whether the student may suitably register for further study in the discipline before remedial work is undertaken.
AB Absent from final examination, but could have passed if exam taken. This is a temporary grade that converts to an F* after the last day of class for the next regular semester unless the student makes up the exam.
FA Failed and absent from exam. The FA grade is given when the undergraduate student did not attend the exam, and could not pass the course regardless of performance on the exam. This would be appropriate for a student that never attended the course or has excessive absences in the course, as well as missing the exam.
IN Work incomplete. This is a temporary grade that converts to F* at the end of eight weeks into the next semester unless the student makes up the incomplete work.
W Withdrew passing. Entered when a student drops after the six-week drop period.

COURSE READINGS

The text for the course is available for purchase from the UNC Student Stores in the Daniels Building (two buildings south of Manning).

SILS Reserves: Copies of the following books are available from the SILS Library on the first floor of Manning Hall (behind the SILS Library help desk):

For the weekly readings, the following labels indicate where specific course readings can be located:

R = Reserves at SILS Library in Manning Hall

C = Course site in Sakai (https://sakai.unc.edu/), where copies of some readings are available (under Course Documents > Readings)

O = Online through UNC license. NOTE: Accessing these materials can require you either to use a computer with a UNC IP address or visit the associated sites through a UNC proxy server. See: Off-Campus Access, http://proxy.lib.unc.edu/setupinfo.html. If you're off campus and want to enter a given page through a UNC proxy server, you can use the following bookmarklet: javascript:location.href='http://libproxy.lib.unc.edu/login?url='+location.href

W = Publicly accessible Web

Some other books on the general themes of the class that you might find interesting (not directly assigned as readings):

An many episodes of Black Mirror.

Week 1 (January 10) - Overview, Structure and Rationale

Discussion of the structure of the class, the topics we'll cover, and why the topics are important to information professionals.

Part 1: Datafication Trends and Activities

Week 2 (January 17) - Internet Activity

Read:

C - Alexander, Neta. "Catered to Your Future Self: Netflix's 'Preductive Personalization' and the Mathematization of Taste." In The Netflix Effect: Technology and Entertainment in the 21st Century, 81-97, edited by Kevin McDonald and Daniel Smith-Rowsey, 2016.

W - Englehardt, Steven and Arvind Narayanan. Princeton Web Census Tracking Results. Web Accountability and Transparency Project, 2016. https://webtransparency.cs.princeton.edu/webcensus/

W - Purewal, Sarah Jacobsson. "Everything you Need to Know about Google's My Activity Page." CNET. July 2016. https://www.cnet.com/au/how-to/everything-you-need-to-know-about-googles-my-activity-page/

O - Vaidhyanathan, Siva. "The Googlization of Us: Universal Surveillance and Infrastructural Imperialism." In The Googlization of Everything: (And Why We Should Worry), 65-86. http://search.lib.unc.edu/search?R=UNCb8655398

Other Related Readings

Week 3 (January 24) - Commerce

Read:

C - Turow, Joseph. "Hunting the Mobile Shopper." In The Aisles Have Eyes: How Retailers Track Your Shopping, Strip Your Privacy, and Define Your Power, 107-143. New Haven, CT: Yale University Press, 2017.

W - Useem, Jerry. "How Online Shopping Makes Suckers of us All. The Atlantic. May 2017. https://www.theatlantic.com/magazine/archive/2017/05/how-online-shopping-makes-suckers-of-us-all/521448/

Other Related Readings

Week 4 (January 31) - Photos and Video

Read:

W - Baker, David. "Photos are Creating a Real-Time Food-Price Index." Wired UK. April 5, 2016. http://www.wired.co.uk/article/premise-app-food-tracking-brazil-philippines

W - Myers, Richard E. "Police-Generated Digital Video: Five Key Questions, Multiple Audiences, and a Range of Answers." 2017. https://www.dropbox.com/s/mel4y65l78a9mgv/Myers,%20BWC%20Framing%20Summary.pdf?dl=0

W - Williams, Timothy, Thomas, James, Jacoby, Samuel, and Damien Cave. "Police Body Cameras: What Do You See?" New York Times. 2016. http://www.nytimes.com/interactive/2016/04/01/us/police-bodycam-video.html

Other Related Readings

Week 5 (February 7) - Sports and Health

Read:

C - Couceiro, Micael S., Duarte Araújo, and Keith Davids. "Internet of Sports: The Rise of Smart Devices for Performance Assessment and Prediction in Sport." In Complex Systems in Sport, International Congress: Linking Theory and Practice, edited by Carlota Torrents, Pedro Passos and Francesc Cos, 30-32. Lausanne, Switzerland: Frontiers, 2017.

C, O - Healey, Glenn. "The New Moneyball: How Ballpark Sensors Are Changing Baseball." Proceedings of the IEEE 105, no. 11 (2017): 1999-2002.

C, O
- Millington, Brad, and Rob Milllington. "'The Datafication of Everything': Toward a Sociology of Sport and Big Data." Sociology of Sport Journal 32 (2015):140-160.

Other Related Readings

Week 6 (February 14) - Built Infrastructure

Read:

C - Enerstvedt, Olga Mironenko. "Aviation Security Technologies." In Aviation Security, Privacy, Data Protection and Other Human Rights: Technologies and Legal Principles, 205-305.  Langhus, Norway: Springer, 2017.

W
- Hamblen, Matt. "Just What IS a Smart City?" ComputerWorld. October 1, 2015. https://www.computerworld.com/article/2986403/internet-of-things/just-what-is-a-smart-city.html

W - "How Rolls-Royce Maintains Jet Engines With the IoT." RTInsights. October 11, 2016. https://www.rtinsights.com/rolls-royce-jet-engine-maintenance-iot/

Other Related Readings

Week 7 (February 21) - Politics and Government

Read:

C,O - Nickerson, David W., and Todd Rogers. "Political Campaigns and Big Data." Journal of Economic Perspectives  28, No. 2 (2014): 51-73.

C,O - Richards, Neil M., and Jonathan H. King. "Three Paradoxes of Big Data." Stanford Law Review 66 (2013): 41-46.

Other Related Readings

Week 8 (February 28) - Education

Read:

W - Alim, Frida, Nate Cardozo, Gennie Gebhart, Karen Gullo, and Amul Kalia. "Spying on Students: School-Issued Devices and Student Privacy." Electronic Frontier Foundation. April 13, 2017. https://www.eff.org/wp/school-issued-devices-and-student-privacy

C - Taylor, Emmeline. "Surveillance Schools: A New Era in Education." In Surveillance Schools: Security, Discipline and Control in Contemporary Education, 15-39. Basingstoke: Palgrave Macmillan, 2013.

Part 2: Access, Use and Analysis of Data

Other Related Readings

Week 9 (March 7) - Technical Foundations

Read:

C - Garfinkel, Simson. "Digital Forensics." American Scientist 101 (2013): 370-377.

C - Goodman, Marc. "Connected, Dependent, and Vulnerable." In Future Crimes: Everything is Connected, Everyone is Vulnerable, and what We Can Do about It, 7-19. New York: Anchor Books, 2015.

Other Related Readings

Week 10 (March 14) - NO CLASS (SPRING BREAK)

Week 11 (March 21) - Predictive Analytics, Machine Learning and Distant Reading

Read:

W - Derman, Emanuel, and Paul Wimott. "The Financial Modelers' Manifesto." January 7, 2009. https://www.uio.no/studier/emner/sv/oekonomi/ECON4135/h09/undervisningsmateriale/FinancialModelersManifesto.pdf

C,O - Kosinskia, Michal, David Stillwell, and Thore Graepel. "Private Traits and Attributes Are Predictable from Digital Records of Human Behavior." Proceedings of the National Academy of Sciences of the United States of America 110, no. 15 (2013): 5802-05.

C,O - Michel, Jean-Baptiste, Yuan Kui Shen, Aviva Presser Aiden, Adrian Veres, Matthew K. Gray, The Google Books Team, Joseph P. Pickett, et al. "Quantitative Analysis of Culture Using Millions of Digitized Books." Science 331 (2011): 176-82.

Other Related Readings

Week 12 (March 28) - Tools and Methods

Read:

C - Church, Kenneth Ward. "Corpus Methods in a Digitized World." In Europhras 2017, edited by R. Mitkov, 3-15: Springer, 2017.

W
- Stephens-Davidowitz, Seth, and Dal Varian. "A Hands-on Guide to Google Data." 2015. http://people.ischool.berkeley.edu/~hal/Papers/2015/primer.pdf

Part 3: Biases, Gaps and Limitations

Other Related Readings

Week 13 (April 4) - Systematic Data Biases, Errors and Corruption

Read:

W - Brennan, Michael. "Can Computers be Racist? Big Data, Inequality, and Discrimination." November 18, 2015. http://www.fordfoundation.org/ideas/equals-change-blog/posts/can-computers-be-racist-big-data-inequality-and-discrimination/

C - Tufekci, Zeynep. "Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls." In Proceedings of the Eighth International AAAI Conference on Weblogs and Social Media, 505-14, 2014.

Other Related Readings

Week 14 (April 11) - Falsification and Resistance

Meet with your peer review partner.

Read:

C - Howe, Daniel C., and Helen Nissenbaum. "Engineering Privacy and Protest: A Case Study of Adnauseam." In 2017 International Workshop on Privacy Engineering – IWPE'17, 2017.

C
- Mitnick, Kevin. "Mastering the Art of Invisibility." In The Art of Invisibility: The World's Most Famous Hacker Teaches you How to Be Safe in the Age of Big Brother and Big Data, 262-277. New York: Little, Brown and Company, 2017.

W - Swartz, Tracey. "Dave Chappelle show's no-phone policy draws mixed emotions from attendees." Chicago Tribune. December 2, 2015. http://www.chicagotribune.com/entertainment/ct-dave-chappelle-cellphone-ban-ent-1203-20151202-story.html

Other Related Readings

Part 4: Synthesis and Conclusions

Week 15 (April 18) - Professional Implications

Week 16 (April 25) - Presentations and Conclusions



Other Related Readings by Week:

Week 2 - Internet Activity

O - Elwood, Sarah, Michael F. Goodchild, and Daniel Z. Sui. "Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice." Annals of the Association of American Geographers 102, no. 3 (2012): 571-90.

W - Madrigal, Alexis C. "How Netflix Reverse Engineered Hollywood." The Atlantic. January 2, 2014. http://www.theatlantic.com/technology/archive/2014/01/hownetflix-reverse-engineered-hollywood/282679/

Narayanan, Arvind, and Dillon Reisman. "The Princeton Web Transparency and Accountability Project." In Transparent Data Mining for Big and Small Data, 45-67: Springer, 2017.

Ronson, Jon. So You've Been Publicly Shamed. New York, NY: Riverhead Books, 2015.

O - Salas-Olmedo, María Henar, Borja Moya-Gómez, Juan Carlos García-Palomares, and Javier Gutiérrez. "Tourists' Digital Footprint in Cities: Comparing Big Data Sources." Tourism Management 66 (2018): 13-25.

Week 3 - Commerce

W - Bishop, Todd. "Amazon Go is finally a go: Sensor-infused store opens to the public Monday, with no checkout lines." GeekWire. January 21, 2018. https://www.geekwire.com/2018/check-no-checkout-amazon-go-automated-retail-store-will-finally-open-public-monday/

W - Maheshwari, Sapna. "Stitch Fix And The New Science Behind What Women Want To Wear." BuzzFeed. September 14, 2014. https://www.buzzfeed.com/sapna/stitch-fix-and-the-new-science-behind-what-women-want-to-wea

O - Papadopoulos, Panagiotis, Nicolas Kourtellis, Pablo Rodriguez Rodriguez, and Nikolaos Laoutaris. "If You Are Not Paying for It, You Are the Product: How Much Do Advertisers Pay to Reach You?". In Proceedings of IMC ’17, 142-56. New York, NY: Association of Computing Machinery, 2017.

Week 4 - Photos and Video

O - Choudhury, Munmun De, Moran Feldman, Sihem Amer-Yahia, Nadav Golbandi, Ronny Lempel, and Cong Yu. "Automatic Construction of Travel Itineraries Using Social Breadcrumbs." In Proceedings of HT’10, June 13–16, 2010, Toronto, Ontario, Canada, 35-44. New York, NY: ACM Press, 2010.

Gibson, James Jerome. The Ecological Approach to Visual Perception. Boston, MA: Houghton Mifflin, 1979.

O - Girardin, Fabien, Josep Blat, Francesco Calabrese, Filippo Dal Fiore, and Carlo Ratti. "Digital Footprinting: Uncovering Tourists with User-Generated Content." Pervasive Computing 7, no. 4 (2008): 36-43.

Levy, David M. Scrolling Forward: Making Sense of Documents in the Digital Age. New York: Arcade, 2001.

W - Mateescu, Alexandra., Rosenblat, Alex, and danah boyd. Police Body-Worn Cameras, Data and Society Research Institute Working Paper, February 2015. http://www.datasociety.net/pubs/dcr/PoliceBodyWornCameras.pdf

W - Stern, Mark Joseph. "Federal Appeals Court: You Have a Constitutional Right to Film Police Officers in Public." Slate. July 7, 2017. http://www.slate.com/blogs/future_tense/2017/07/07/third_circuit_affirms_the_constitutional_right_to_record_police_officers.html

W - Venneti, Satya. "Revealing True Emotions Through Micro-Expressions: A Machine Learning Approach." January 15, 2018. https://insights.sei.cmu.edu/sei_blog/2018/01/revealing-true-emotions-through-micro-expressions-a-machine-learning-approach.html

W - Yokum, David, Anita Ravishankar, and Alexander Coppock. ”Evaluating the Effects of Police Body-Worn Cameras: A Randomized Controlled Trial.” The Lab @ DC. October 20, 2017.  http://bwc.thelab.dc.gov/TheLabDC_MPD_BWC_Working_Paper_10.20.17.pdf


Week 5 - Sports and Health

C, O - Baerg, Andrew. "Big Data, Sport, and the Digital Divide: Theorizing How Athletes Might Respond to Big Data Monitoring." Journal of Sport and Social Issues 41, no. 1 (2017): 3-20.

C, O - Colás, Yago. "The Culture of Moving Dots: Toward a History of Counting and of What Counts in Basketball." Journal of Sport History 44, no. 2 (2017): 336-49.

Jakicic, John M., Kelliann K. Davis, Renee J. Rogers, Wendy C. King, Marsha D. Marcus, Diane Helsel, Amy D. Rickman, Abdus S. Wahed, and Steven H. Belle. "Effect of Wearable Technology Combined with a Lifestyle Intervention on Long-Term Weight Loss: The Idea Randomized Clinical Trial." Journal of the American Medical Association 316, no. 11 (2016): 1161-71.

Ruckenstein, Minna, and Natasha Dow Schüll. "The Datafication of Health." Annual Review of Anthropology 46 (2017): 261-78.

Week 6 - Built Infrastructure

O - Ang, Li-Minn, Kah Phooi Seng, Adamu Murtala Zungeru, and Gerald K. Ijemaru. "Big Sensor Data Systems for Smart Cities." IEEE Internet of Things Journal 4, no. 5 (2017): 1259-71.

Froehlich, Jon, Joachim Neumann, and Nuria Oliver. "Sensing and Predicting the Pulse of the City through Shared Bicycling." In Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence (Ijcai-09), 1420-26, 2009.

Week 7 - Politics and Government

W - Reitman, Rainey. "Who Has Your Back? Government Data Requests 2017." Electronic Frontier Foundation. July 10, 2017. https://www.eff.org/who-has-your-back-2017

Taylor, Linnet, and Dennis Broeders. "In the Name of Development: Power, Profit and the Datafication of the Global South." Geoforum 64 (2015): 229-37.

Week 8 - Education


Week 9 - Technical Foundations

W - "How The Intercept Outed Reality Winner." Errata Security. June 5, 2017. http://blog.erratasec.com/2017/06/how-intercept-outed-reality-winner.html

W - Moxley, R. Scott. "Best Buy Geek Squad Informant Use Has FBI on Defense in Child-Porn Case." OC Weekly. January 4, 2017. http://www.ocweekly.com/news/best-buy-geek-squad-informant-use-has-fbi-on-defense-in-child-porn-case-7794252

Week 11 - Predictive Analytics, Machine Learning and Distant Reading

O - Cukier, Kenneth, and Viktor Mayer-Schoenberger. "The Rise of Big Data: How It's Changing the Way We Think About the World." Foreign Affairs 28 (2013): 28-40.

Jänicke, S., G. Franzini, M. F. Cheema, and G. Scheuermann. "On Close and Distant Reading in Digital Humanities: A Survey and Future Challenges." Paper presented at the Eurographics Conference on Visualization (EuroVis), 2015.

O - McCulloch, Jude and Dean Wilson. Pre-Crime: Pre-Emption, Precaution and the Future. New York, NY: Routledge, 2016. http://search.lib.unc.edu/search?R=UNCb8617446

O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy: New York, NY: Crown, 2016.

Powles, Julia, and Hal Hodson. "Google Deepmind and Healthcare in an Age of Algorithms." Health and Technology  (2017).

Sidhu, Dawinder S. "Moneyball Sentencing." Boston College Law Review 56 (2015): 671-731.

Week 12 - Tools and Methods

Kilgarriff, Adam. "Googleology Is Bad Science." Computational Linguistics 33, no. 1 (2007): 147-51.

Week 13 - Systemic Data Biases, Errors and Corruption

Bayerl, Petra Saskia, and Babak Akhgar. "Online Surveillance Awareness as Impact on Data Validity for Open-Source Intelligence?". In Proceedings of Icgs3, 15-20: Springer, 2015.

Calude, Cristian S., and Giuseppe Longo. "The Deluge of Spurious Correlations in Big Data." Foundations of Science 22, no. 3 (2017): 595-612.

W - Cesare, Nina, Hedwig Lee, Tyler McCormick, Emma Spiro, and Emilio Zagheni. "Promises and Pitfalls of Using Digital Traces for Demographic Research." 2016. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2839585

O - Dubrofsky, Rachel E., and Shoshana Amielle Magnet, eds. 2015. Feminist Surveillance Studies. Durham, NC: Duke University Press. http://search.lib.unc.edu/search?R=UNCb8279955

Noble, Safiya Umoja. "Google Search: Hyer-Visibility as a Means of Rendeirng Black Women and Girls Invisible." InVisible Culture 19 (2013).

Pariser, Eli. The Filter Bubble: What the Internet Is Hiding from You.  New York: Penguin Press, 2011.

Penney, Jonathon W. "Internet Surveillance, Regulation, and Chilling Effects Online: A Comparative Case Study." Internet Policy Review 6, no. 2 (2017).

W - "Victoria Police to Withdraw 8000 Traffic Tickets After Roadside Cameras Infected with WannaCry Virus." Yahoo! News. June 24, 2017. https://uk.news.yahoo.com/victoria-police-withdraw-8000-traffic-070042414.html

Week 14 - Falsification and Resistance

Bayerl, Petra Sakia, and Babak Akhgar. "Surveillance and Falsification Implications for Open Source Intelligence Investigations." Communications of the ACM 58, no. 8 (2015): 62-69.

Brunton, Finn, and Helen Fay Nissenbaum. Obfuscation: A User's Guide for Privacy and Protest.  Cambridge, MA: MIT Press, 2015.

W - Larson, Quincy. "How to encrypt your entire life in less than an hour." freeCodeCamp. November 9, 2016. https://medium.freecodecamp.org/tor-signal-and-beyond-a-law-abiding-citizens-guide-to-privacy-1a593f2104c3

Luan, Fujun, Sylvain Paris, Eli Shechtman, and Kavita Bala. "Deep Photo Style Transfer." 2017.

Marthews, Alex, and Catherine Tucker. "Government Surveillance and Internet Search Behavior." 2017.

W - O'Brien, Sean, and Michael Kwet. "Android Users: To Avoid Malware, Try the F-Droid App Store." Wired. January 21, 2018. https://www.wired.com/story/android-users-to-avoid-malware-ditch-googles-app-store/

Schaub, Florian, Aditya Marella, Pranshu Kalvani, Blase Ur, Chao Pan, Emily Forney, and Lorrie Faith Cranor. "Watching Them Watching Me: Browser Extensions’ Impact on User Privacy Awareness and Concern." In Proceedings of Usec ’16, 21 February 2016, San Diego, Ca: Internet Society, 2016.

Zhu, Jun-Yan, Taesung Park, Phillip Isola, and Alexei A. Efros. "Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks." 2017.