Welcome to the Search Studies research group

Research on commercial search engines
from a user perspective.

We study how users interact with search engines and how this affects society by applying methods from information science, data science, and the social sciences.

Result Assessment Tool

We develop research software that allows comparing results from commercial search engines.

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We aim to understand the influence of search engine optimization (SEO) on results in commercial search engines.

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Search Ads

We address the question of how contextual advertisements influence information seeking.

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Trust in Search Engines

Doctoral research project on the extent and adequacy of user trust in commercial search engines.

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Knowledge gain

Doctoral research project on the influence of search engine marketing (SEM) on user knowledge gain.

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See a full list of our research projects.

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About us

At the Search Studies research group, we focus on understanding user interaction with commercial search engines and how it affects knowledge acquisition in society.

Our research is mainly empirical, applying methods from information science, data science and the social sciences.

Our empirical research projects rest on two pillars:

  • Search engine data analysis, collecting and analysing data from commercial search engines (data science, applied machine learning).
  • Understanding information-seeking behaviour through conducting user studies in different settings (information science), ranging from large, representative online surveys to behavioural studies in the lab.

The results from our research provide a deeper understanding of how commercial search engines influence what results users will consider in their information searches and, in consequence, which information they consider when searching for societal relevant topics. Our research informs information literacy interventions and regulation of search engines as information gatekeepers.

Read more about the research group in our article “The Search Studies Group at Hamburg University of Applied Sciences“, published in Datenbank Spektrum 2021.

Tuhina Kumar


Sophia Bosnak

Student Assistant

Quang Duc Tran

Student Assistant

Metehan Günes

Student Assistant