Webtrack – Desktop Extension for Tracking Users’ Browsing Behaviour using Screen-Scraping

Aigenseer, V.; Urman, Aleksandra; Christner, C.; Maier, Michaela; Adam, Silke; Makhortykh, Mykola; Gil-Lopez, T. (24 September 2019). Webtrack – Desktop Extension for Tracking Users’ Browsing Behaviour using Screen-Scraping (Unpublished). In: GESIS Computational Social Science (CSS) Seminar. Mannheim. 24.09.2019.

Social science researchers agree on the relevance of tracing citizens’ information usage on the Internet and analyzing how the algorithmic selection processes influence what they receive online. Yet, many scholars still rely on classical survey research when trying to analyze online information behavior, although this research has shown to be insufficient due to social desirability concerns and the users’ limited capacities to remember their online behavior (Prior 2009; Scharkow 2016). Social scientists who already use computational tools that automatically register online information behavior, often rely on web analytics software (e.g. Leiner, Scherr & Bartsch 2016). Such software, however, requires the modification of the original web content of targeted websites or focus on one technological interface (e.g. www.fbforschung.de/). For broader tracking efforts, some academic tools are just evolving (e.g. Newstracker see Kleppe & Otto, 2017; Roxy see Menchen-Trevino & Karr, 2012, Web Historian see Menchen-Trevino, 2016) whereas others have relied on market researchers’ tools. Most approaches, however, only allow to identify the URLs without capturing the content information (for exceptions see Dvir-Gvirsman, Tsfati, & Menchen-Trevino, 2016; Bodo et al., 2017). This is where the project of Prof. Maier and her colleagues sets in. They are developing a tracking tool that allows to track online information behavior across different platforms and extract the content a user actually sees for the further analysis. The latter feature is very important as such screen-scraping allows Prof. Maier and her colleagues to observe the algorithmically personalized content each user is exposed to. In contrast to most commercial solutions, this tool strongly focuses on privacy issues allowing different privacy options. WebTrack is a browser extension (so far adapted for Chrome and Firefox), which runs on desktop devices. In the presentation Prof. Maier and her colleagues will demonstrate how the tool works, and which chances and challenges she and her colleagues tackle.

Item Type:

Conference or Workshop Item (Speech)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Social Sciences
03 Faculty of Business, Economics and Social Sciences > Social Sciences > Institute of Mass Communication Studies

UniBE Contributor:

Urman, Aleksandra; Maier, Michaela; Adam, Silke and Makhortykh, Mykola

Subjects:

300 Social sciences, sociology & anthropology

Language:

English

Submitter:

Lena Floriana Studer

Date Deposited:

04 Feb 2020 10:19

Last Modified:

04 Feb 2020 10:19

URI:

https://boris.unibe.ch/id/eprint/139219

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