aoir 2016 digital methods workshop - tracking the trackers

An AoIR Digital Methods Workshop

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

Tracking the Trackers

Agenda

1. Introduction: Trackers2. Tracker tracker tool3. Example project: Like Economy4. Methods walkthrough5. 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 & sites2. Website (URL) collection making: existing

expert list (e.g. alexa.com)3. Input collection into Tracker Tracker tool4. Visualise results with Gephi5. 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 exh5. 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 > OK2. Layout > Choose a Layout > Force Atlas 2

a. Scaling: 30b. Dissuade: yesc. 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 size5. Layout > Choose a Layout > Label adjust6. Color > Nodes > Attribute > Type7. Preview > Presets > Default Straight

a. Node Labels Arial 10> Refresh8. Export > SVG/PDF/PNG9. 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

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/>