Sebastian Schultheiß

Researcher

Sebastian Schultheiß is a Research Associate at the Hamburg University of Applied Sciences (HAW Hamburg) within the Search Studies research group. As an information scientist, his research focuses on commercial search engines from a user perspective, specifically examining how search engine marketing, search engine optimization (SEO), and AI-generated content influence user behavior and society. His research has been published in leading journals such as the Journal of the Association for Information Science and Technology (JASIST), Journal of Documentation, and Journal of Information Science.

His academic work investigates the development and empirical testing of information search behavior models, with a particular interest in how commercial influences affect user knowledge gain. To conduct this research, he employs a diverse range of social research methods, including eye-tracking, laboratory behavioral studies, interviews, and representative online surveys. He is also a key contributor to the sustainability of the Result Assessment Tool (RAT), a specialized software toolkit designed to empower search engine data analysis.

Sebastian Schultheiß recently completed his doctoral candidacy at the Humboldt University of Berlin with the distinction of summa cum laude.

Beyond his research, he is actively involved in the academic community as a steering committee member of the Search Engines and Society Network (SEASON) and as a frequent peer reviewer for major conferences including CHIIR, ECIR, and the ASIS&T Annual Meeting. At HAW Hamburg, he teaches Bachelor’s and Master’s level courses on topics ranging from the quality of AI-generated information to information search behavior and research data management. He is a recipient of the Gerhard Lustig Award for the best Master’s Thesis in Information Science (2017–2020).

Sebastian’s curriculum vitae (CV) as of December 2025:

Publications

Articles in refereed journals

Schultheiß, S.; Lewandowski, D. (2025). Becoming visible with limited resources: Non-profit journalists’ perspectives on search engine optimization. PLoS One 20(4): e0322573. https://doi.org/10.1371/journal.pone.0322573

Häußler, H.; Schultheiß, S.; Lewandowski, D. (2023). Is googling risky? A study on risk perception and experiences of adverse consequences in web search. Journal of the Association for Information Science and Technology, 1-14. https://doi.org/10.1002/asi.24802

Schultheiß, S.; Lewandowski, D.; Mach, S.; Yagci, N. (2023). Query sampler: generating query sets for analyzing search engines using keyword research tools. PeerJ Computer Science. https://doi.org/10.7717/peerj-cs.1421

Lewandowski, D., & Schultheiß, S. (2022). Public awareness and attitudes towards search engine optimization. Behaviour & Information Technology, 1–20. https://doi.org/10.1080/0144929X.2022.2056507; Preprint

Schultheiß, S.; Lewandowski, D. (2021). ‘Outside the industry, nobody knows what we do’: SEO as seen by search engine optimizers and content providers. Journal of Documentation 77(2), 542-557. https://doi.org/10.1108/JD-07-2020-0127

Schultheiß, S.; Lewandowski, D. (2021). How users’ knowledge of advertisements influences their viewing and selection behaviour in search engines. Journal of the Association for Information Science and Technology 72(3), 285-301. https://doi.org/10.1002/asi.24410

Lewandowski, D.; Sünkler, S.; Schultheiß, S.; Häußler, H.; Spree, U.; Behnert, C. (2021). The Search Studies Group at Hamburg University of Applied Sciences. Datenbank Spektrum. https://doi.org/10.1007/s13222-021-00375-x

Schultheiß, S.; Lewandowski, D. (2021). Misplaced trust? The relationship between trust, ability to identify commercially influenced results, and search engine preference. Journal of Information Science. https://doi.org/10.1177/01655515211014157

Lewandowski, D.; Sünkler, S.; Schultheiß, S. (2020). Studies on Search: Designing Meaningful IIR Studies on Commercial Search Engines. Datenbank Spektrum 20(1), 5-15. https://doi.org/10.1007/s13222-020-00331-1

Schultheiß, S.; Linhart, A.; Behnert, C.; Rulik, I.; Lewandowski, D. (2020). Known-item searches and search tactics in library search systems: Results from four transaction log analysis studies. Journal of Academic Librarianship 46(5), article 102202. https://doi.org/10.1016/j.acalib.2020.102202

Schultheiß, S., Sünkler, S., & Lewandowski, D. (2018). We still trust in Google, but less than 10 years ago: an eye-tracking study. Information Research 23(3). Preprint

Kerkmann, F., Sünkler, S., & Schultheiß, S. (2017). Die Suche nach dem „Wie…“ – Tutorials als Gegenstand der Suche. Wissenschaft & Praxis 68(1), 58–66.

Articles in proceedings

Sünkler S.; Yagci, N.; Schultheiß, S.; von Mach, S.; Lewandowski, D.; (2024) Result Assessment Tool Software to Support Studies Based on Data from Search Engines In: Part of the book series: Lecture Notes in Computer Science https://link.springer.com/chapter/10.1007/978-3-031-56069-9_19

Schultheiß, S. (2023). How search engine marketing influences user knowledge gain. Development and empirical testing of an information search behavior model. CHIIR '23: ACM SIGIR Conference on Human Information Interaction and Retrieval. https://doi.org/10.1145/3576840.3578297; Preprint

Schultheiß, S.; Sünkler, S.; Yagci, N.; Sygulla, D.; von Mach, S.; Lewandowski, D.; (2023). Simplify your Search Engine Research : wie das Result Assessment Tool (RAT) Studien auf der Basis von Suchergebnissen unterstützt. In: Proceedings des 17. Internationalen Symposiums für Informationswissenschaft (ISI 2023), 429-437. PDF proceedings; PDF article

Schultheiß, S.; Sünkler, S.; Yagci, N.; Sygulla, D.; von Mach, S.; Lewandowski, D.; (2023). Result Assessment Tool (RAT): A Software Toolkit for Conducting Studies Based on Search Results. In: Proceedings of the Association for Information Science and Technology https://doi.org/10.1002/pra2.972

Sünkler, S.; Yagci, N.; Sygulla, D.; von Mach, S.; Schultheiß, S.; Lewandowski, D.; (2023). Result Assessment Tool (RAT): Software-Toolkit für die Durchführung von Studien auf der Grundlage von Suchergebnissen. In: Proceedings des 17. Internationalen Symposiums für Informationswissenschaft (ISI 2023), 438-444. PDF proceedings ; PDF article

Häußler, H.; Schultheiß, S.; Sünkler, S.; Lewandowski, D. (2022). From knowing to showing : Using marking tasks to demonstrate information literacy in practice. 2022 ASIS&T 24-Hour Conference. https://doi.org/10.5281/zenodo.6406802

Lewandowski, D., Schultheiß, S., Sünkler, S. (2022). Einﬂüsse auf die Ergebnisse kommerzieller Suchmaschinen: Modellbildung und empirische Ergebnisse. Informationswissenschaft im Wandel. Wissenschaftliche Tagung 2022 (IWWT22), Düsseldorf. PDF proceedings; PDF article

Schultheiß, S.; Häußler, H.; Lewandowski, D. (2022). Does Search Engine Optimization come along with high-quality content?: A comparison between optimized and non-optimized health-related web pages. CHIIR '22: ACM SIGIR Conference on Human Information Interaction and Retrieval, 123–134. https://doi.org/10.1145/3498366.3505811; Preprint; YouTube

Sünkler, S., Yagci, N., Sygulla, D., von Mach, S., Schultheiß, S. Lewandowski, D. (2022). Result Assessment Tool: Software zur Durchführung von Studien auf der Basis von Suchergebnissen. Informationswissenschaft im Wandel. Wissenschaftliche Tagung 2022 (IWWT22), Düsseldorf. PDF proceedings; PDF article

Schultheiß, S.; Lewandowski, D. (2021). (Un)bekannte Akteure auf der Suchergebnisseite? Ein Vergleich zwischen selbst eingeschätzter und tatsächlich vorhandener Suchmaschinenkompetenz deutscher InternetnutzerInnen. In: T. Schmidt, C. Wolff (Hrsg.): Information between Data and Knowledge. Information Science and its Neighbors from Data Science to Digital Humanities. Proceedings of the 16th International Symposium of Information Science (ISI 2021), 218-246. https://www.doi.org/10.5283/epub.44946

Schultheiß, S. (2021). Der Einfluss des Verständnisses von Suchmaschinenwerbung auf das Rechercheverhalten am PC und am mobilen Endgerät: Eine Nutzerstudie [Extended Abstract]. In: T. Schmidt, C. Wolff (Hrsg.): Information between Data and Knowledge. Information Science and its Neighbors from Data Science to Digital Humanities. Proceedings of the 16th International Symposium of Information Science (ISI 2021), 461-467. https://www.doi.org/10.5283/EPUB.44964

Articles in magazines

Schultheiß, S., & Lewandowski, D. (2021). Google search results—They’re all the same, right?. Information Matters. Vol.1, Issue 11. https://informationmatters.org/2021/11/google-search-results-theyre-all-the-same-right/

Open data

Schultheiß, S., & Lewandowski, D. (2022). Data set of a representative online survey on search engines with a focus on search engine optimization (SEO): a cross-sectional study. F1000Research, 11(376). https://doi.org/10.12688/f1000research.109662.2

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