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AoIR 2016 Digital Methods Workshop - Tracking the Trackers

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Anne Helmond, Carolin Gerlitz, Esther Weltevrede and Fernando van der Vlist

Social media plugins, including social buttons, enable users to engage with platform actions such as liking, sharing or tweeting across the web, but at the same time function as third-party objects tracking users across external websites and apps and feeding data back to the associated platforms. In this workshop we will explore how to detect, map and analyze such tracker networks. We will demonstrate the Tracker Tracker tool, developed at the University of Amsterdam, which is able to scan sets of websites for trackers and output the results in a graph file that can subsequently be used in the free network visualisation software application Gephi.

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AoIR 2016 Digital Methods Workshop - Tracking the Trackers

  1. 1. An AoIR Digital Methods Workshop Anne Helmond, Carolin Gerlitz, Fernando van der Vlist, and Esther Weltevrede Tracking the Trackers
  2. 2. Agenda 1. Introduction: Trackers 2. Tracker tracker tool 3. Example project: Like Economy 4. Methods walkthrough 5. Example cases
  3. 3. 1. Introduction: Trackers
  4. 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. 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. 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.
  7. 7. 2. Tracker tracker tool
  8. 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. 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. 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. 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.
  12. 12. Facebook trackers
  13. 13. 4. Methods walkthrough
  14. 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. 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. 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.
  17. 17. Porn-specific trackers
  18. 18. 5. Example cases
  19. 19. Jihadi websites Key finding: Jihad website use advertising platforms of the major Western tech companies
  20. 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. 21. Slate - Backend trackers & widgets visualization
  22. 22. Tracker’s Guide
  23. 23. 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.
  24. 24. 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
  25. 25. 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/>

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