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AoIR 2016 Digital Methods Workshop - Tracking the Trackers

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This document summarizes an AoIR Digital Methods Workshop on tracking technologies on the web. It introduces different types of trackers like cookies, widgets and advertising trackers that collect data as users browse websites. The workshop demonstrates the Tracker Tracker tool to analyze which trackers are present on lists of websites and identify connections between sites and trackers. An example project analyzing social media platform trackers on the 1000 most visited websites found widespread tracking by Facebook and other companies. The workshop provides methods for analyzing tracker prevalence and visualizing results to study the invisible infrastructures of the web.

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An AoIR Digital Methods Workshop Anne Helmond, Carolin Gerlitz, Fernando van der Vlist, and Esther Weltevrede Tracking the Trackers
Agenda 1. Introduction: Trackers 2. Tracker tracker tool 3. Example project: Like Economy 4. Methods walkthrough 5. Example cases
1. Introduction: Trackers
Tracking “For every explicit action of a user, there are probably 100+ implicit data points from usage; whether that is a page visit, a scroll etc.” (Berry 2011: 152)
Every time a web user requests a website, a series of tracking features are enabled: cookies, widgets, advertising trackers, analytics, beacons etc. First party (from website) vs. third party tracker (e.g. Facebook, Twitter, Google). Purpose: From functionality to profiling. Tracking technologies
Tracker blocking Ghostery: Browser plugin which detects and allows to block the ‘invisible’ web and prevents a ‘digital footprint’. Detection via tracker library/code snippets [reg ex]. Detecting around 2295 trackers. Not uncontroversial: started as NGO, then bought by analytics company Evidon in 2010.
2. Tracker tracker tool
DMI Tracker Tracker Tracker Tracker: tool built on top of Ghostery by the Digital Methods Initiative (2012). Allows to detect which trackers are present on lists of websites & create a network view. “Repurposing analytical capacities” of privacy app: digital research methods paired with platform & software studies.
3. Example project: Like Economy Gerlitz, Carolin, and Anne Helmond. 2013. “The Like Economy: Social Buttons and the Data- Intensive Web.” New Media & Society 15 (8): 1348–65. doi:10.1177/1461444812472322.
Like Economy Starting point: social media widgets place cookies (Gerlitz & Helmond 2013). These cookies track both platform users and anyone else on the web. All web users potentially feed data into platforms through cookies. RQ: How pervasive are platform cookies on the most visited websites of the web?
Like Economy: Method 1. Create a collection of 1000 most-visited websites based on Alexa.com data. 2. Input into the Tracker Tracker tool. 3. Visualise results with Gephi. 4. Colour-code based on platform.
Facebook trackers
4. Methods walkthrough
Methodological summary 1. Research question: type of tracker & sites 2. Website (URL) collection making: existing expert list (e.g. alexa.com) 3. Input collection into Tracker Tracker tool 4. Visualise results with Gephi 5. Analyse results + add layers
Tracking exercise 1. What kind of sites do you want to study? 2. Get access to the collections made with Alexa.com: http://tiny.cc/TrackURLs. 3. Enter the list into the Tracker Tracker tool. Settings: Only look at specified pages. 4. Save > Output > GEFX (Gephi). a. Alternative: Save > Output > CSV exh 5. Open in Gephi, use colour settings to visually distinguish between different tracking services/types. a. Alternative: visualize CSV (e.g. bar graphs) with Google Sheets.
Tracking exercise Gephi instructions*: 1. New Project > Open Graph File > OK 2. Layout > Choose a Layout > Force Atlas 2 a. Scaling: 30 b. Dissuade: yes c. Prevent Overlap: yes 3. Appearance > Nodes > Size > Attribute > Degree > Min size: 5 Max size: 30 (you can play with these settings). 4. Show Node labels. Scale node labels to node size 5. Layout > Choose a Layout > Label adjust 6. Color > Nodes > Attribute > Type 7. Preview > Presets > Default Straight a. Node Labels Arial 10> Refresh 8. Export > SVG/PDF/PNG 9. Data visualization interpretation These settings work well for the top 25 adult sites. All Gephi settings depend on the graph (e.g. amount of nodes/type of algorithm needed for analysis). There are no “universal” settings.
Porn-specific trackers
5. Example cases
Jihadi websites Key finding: Jihad website use advertising platforms of the major Western tech companies
Historical tracking analysis using the Internet Archive Studying the website as an ecosystem embedded in techno-commercial configurations over time through its archived source code (Helmond 2015)
Slate - Backend trackers & widgets visualization
Tracker’s Guide
AoIR 2016 Digital Methods Workshop - Tracking the Trackers
AoIR 2016 Digital Methods Workshop - Tracking the Trackers
Key questions Limits of repurposing analytical capacities of existing devices. What data is actually being collected? Study invisible participation in data flows. Study media concentration. Alternative spatialities of the web - tracker origins and national ecologies. Insights into invisible infrastructures of the web.
End! Thank you. Anne Helmond, University of Amsterdam. Carolin Gerlitz, University of Siegen. Fernando van der Vlist, University of Siegen. Esther Weltevrede, University of Amsterdam. https://digitalmethods.net
References Gerlitz, Carolin, and Anne Helmond. “The Like Economy: Social Buttons and the Data-Intensive Web.” New Media & Society 15.8 (2013): 1348–1365. <http://nms.sagepub.com/content/15/8/1348>. Helmond, Anne. “Historical Website Ecology. Analyzing Past States of the Web Using Archived Source Code.” Web 25: Histories from the First 25 Years of the World Wide Web. Ed. Niels Brügger. New York: Peter Lang Publishing, forthcoming. See Dropbox. Helmond, Anne. “Website Ecologies: Redrawing the Boundaries of a Website.” The Web as Platform: Data Flows in Social Media. PhD thesis. Amsterdam: University of Amsterdam, 2015. 132–165. <http://dare.uva.nl/record/1/485895>. van der Velden, Lonneke. “The Third Party Diary: Tracking the Trackers on Dutch Governmental Websites.” NECSUS. European Journal of Media Studies 3.1 (2014): 195–217. <http://www.necsus-ejms.org/third-party-diary-tracking-trackers-dutch-governmental-websites-2/>

More Related Content

AoIR 2016 Digital Methods Workshop - Tracking the Trackers

  • 1. An AoIR Digital Methods Workshop Anne Helmond, Carolin Gerlitz, Fernando van der Vlist, and Esther Weltevrede Tracking the Trackers
  • 2. Agenda 1. Introduction: Trackers 2. Tracker tracker tool 3. Example project: Like Economy 4. Methods walkthrough 5. Example cases
  • 4. Tracking “For every explicit action of a user, there are probably 100+ implicit data points from usage; whether that is a page visit, a scroll etc.” (Berry 2011: 152)
  • 5. Every time a web user requests a website, a series of tracking features are enabled: cookies, widgets, advertising trackers, analytics, beacons etc. First party (from website) vs. third party tracker (e.g. Facebook, Twitter, Google). Purpose: From functionality to profiling. Tracking technologies
  • 6. Tracker blocking Ghostery: Browser plugin which detects and allows to block the ‘invisible’ web and prevents a ‘digital footprint’. Detection via tracker library/code snippets [reg ex]. Detecting around 2295 trackers. Not uncontroversial: started as NGO, then bought by analytics company Evidon in 2010.
  • 8. DMI Tracker Tracker Tracker Tracker: tool built on top of Ghostery by the Digital Methods Initiative (2012). Allows to detect which trackers are present on lists of websites & create a network view. “Repurposing analytical capacities” of privacy app: digital research methods paired with platform & software studies.
  • 9. 3. Example project: Like Economy Gerlitz, Carolin, and Anne Helmond. 2013. “The Like Economy: Social Buttons and the Data- Intensive Web.” New Media & Society 15 (8): 1348–65. doi:10.1177/1461444812472322.
  • 10. Like Economy Starting point: social media widgets place cookies (Gerlitz & Helmond 2013). These cookies track both platform users and anyone else on the web. All web users potentially feed data into platforms through cookies. RQ: How pervasive are platform cookies on the most visited websites of the web?
  • 11. Like Economy: Method 1. Create a collection of 1000 most-visited websites based on Alexa.com data. 2. Input into the Tracker Tracker tool. 3. Visualise results with Gephi. 4. Colour-code based on platform.
  • 14. Methodological summary 1. Research question: type of tracker & sites 2. Website (URL) collection making: existing expert list (e.g. alexa.com) 3. Input collection into Tracker Tracker tool 4. Visualise results with Gephi 5. Analyse results + add layers
  • 15. Tracking exercise 1. What kind of sites do you want to study? 2. Get access to the collections made with Alexa.com: http://tiny.cc/TrackURLs. 3. Enter the list into the Tracker Tracker tool. Settings: Only look at specified pages. 4. Save > Output > GEFX (Gephi). a. Alternative: Save > Output > CSV exh 5. Open in Gephi, use colour settings to visually distinguish between different tracking services/types. a. Alternative: visualize CSV (e.g. bar graphs) with Google Sheets.
  • 16. Tracking exercise Gephi instructions*: 1. New Project > Open Graph File > OK 2. Layout > Choose a Layout > Force Atlas 2 a. Scaling: 30 b. Dissuade: yes c. Prevent Overlap: yes 3. Appearance > Nodes > Size > Attribute > Degree > Min size: 5 Max size: 30 (you can play with these settings). 4. Show Node labels. Scale node labels to node size 5. Layout > Choose a Layout > Label adjust 6. Color > Nodes > Attribute > Type 7. Preview > Presets > Default Straight a. Node Labels Arial 10> Refresh 8. Export > SVG/PDF/PNG 9. Data visualization interpretation These settings work well for the top 25 adult sites. All Gephi settings depend on the graph (e.g. amount of nodes/type of algorithm needed for analysis). There are no “universal” settings.
  • 19. Jihadi websites Key finding: Jihad website use advertising platforms of the major Western tech companies
  • 20. Historical tracking analysis using the Internet Archive Studying the website as an ecosystem embedded in techno-commercial configurations over time through its archived source code (Helmond 2015)
  • 21. Slate - Backend trackers & widgets visualization
  • 25. Key questions Limits of repurposing analytical capacities of existing devices. What data is actually being collected? Study invisible participation in data flows. Study media concentration. Alternative spatialities of the web - tracker origins and national ecologies. Insights into invisible infrastructures of the web.
  • 26. End! Thank you. Anne Helmond, University of Amsterdam. Carolin Gerlitz, University of Siegen. Fernando van der Vlist, University of Siegen. Esther Weltevrede, University of Amsterdam. https://digitalmethods.net
  • 27. References Gerlitz, Carolin, and Anne Helmond. “The Like Economy: Social Buttons and the Data-Intensive Web.” New Media & Society 15.8 (2013): 1348–1365. <http://nms.sagepub.com/content/15/8/1348>. Helmond, Anne. “Historical Website Ecology. Analyzing Past States of the Web Using Archived Source Code.” Web 25: Histories from the First 25 Years of the World Wide Web. Ed. Niels Brügger. New York: Peter Lang Publishing, forthcoming. See Dropbox. Helmond, Anne. “Website Ecologies: Redrawing the Boundaries of a Website.” The Web as Platform: Data Flows in Social Media. PhD thesis. Amsterdam: University of Amsterdam, 2015. 132–165. <http://dare.uva.nl/record/1/485895>. van der Velden, Lonneke. “The Third Party Diary: Tracking the Trackers on Dutch Governmental Websites.” NECSUS. European Journal of Media Studies 3.1 (2014): 195–217. <http://www.necsus-ejms.org/third-party-diary-tracking-trackers-dutch-governmental-websites-2/>

Editor's Notes

  1. C
  2. What are these elements that track our online behaviour? What data do they collect? What happens with the data? What does that teach us about the data-intensive web?
  3. In response to the proliferation of trackers, a variety of anti-tracker devices has emerged. Ghostery: make money from donations & ghostrank. “We take that information, add our analysis, and sell it to brands and websites to help them evaluate their relationships with their marketing partners. Some ad tech companies use the data to compare themselves to their competition, while other research firms buy it to learn more about the industry. We also provide data to consumer advocacy groups like the Better Business Bureau (BBB), journalists writing stories about privacy, and students and activists involved in related projects and papers.”
  4. Makes use of ghostery database, code snippet, matching.
  5. To detect the relative presence of Facebook tracking tools in the web, we took the top 1000 global websites according to Alexa and identified fingerprints of different tracking devices such as analytics, ad programs, widgets, social plugins. The first map highlights the websites using Facebook Social Plugins and Facebook Connect.
  6. In our sample from 2012, around 18% of all websites feature at least one of these connections to Facebook, allowing users to engage with their content via Facebook features and ena- bling multiple data flows in the back end. >>> Interesting to test if presence of platform trackers has grown.
  7. the example project shows a particular approach
  8. >> Walkthrough starts
  9. >> Walkthrough, see Google Doc - These settings really depend on your graph - I have adjusted the settings to work with the top25 adult sites.
  10. >> Walkthrough, see Google Doc - These settings really depend on your graph - I have adjusted the settings to work with the top25 adult sites.
  11. with all that in mind we turn to a small exercise
  12. How do alternative actors participate in the global advertising economy
  13. Develop a method to study the ecosystem of a website over time, a website is embedded in a techno-commercial configuration - in which trackers play a role. Media concentration?
  14. Historical trackers - INTERNET ARCHIVE
  15. Further developing the notion of how websites are informed by third parties - we created this guide - biological
  16. Here we focused on the question of who owns these trackers and what kind of data do they collect (based on privacy policies etc) and which countries these trackers are located in. role of US prominent, raising questions about where data is stored.
  17. Add references Historical trackers Anne Lonneke’s paper