Top

Datenbank-Spektrum

Published in:

22-06-2021 | Datenbankgruppen vorgestellt

The Search Studies Group at Hamburg University of Applied Sciences

Authors: Dirk Lewandowski, Sebastian Sünkler, Sebastian Schultheiß, Helena Häußler, Ulrike Spree, Christiane Behnert

Published in: Datenbank-Spektrum | Issue 2/2021

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

We present an overview of the work of the Search Studies research group, focusing on commercial search engines from a user perspective. This encompasses studying what users of these search engines get to see on the result pages, how users interact with search engines, and the effect both have on knowledge acquisition in society. Our research combines search engine data analysis, by collecting and analysing data from commercial search engines (data science), with 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 employing, amongst others, eye-tracking.

previous article In-Depth Analysis of OLAP Query Performance on Heterogeneous Hardware

next article Dissertationen

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Datenbank-Spektrum

Datenbank-Spektrum ist das offizielle Organ der Fachgruppe Datenbanken und Information Retrieval der Gesellschaft für Informatik (GI) e.V. Die Zeitschrift widmet sich den Themen Datenbanken, Datenbankanwendungen und Information Retrieval.

inform now

Buckland M (2017) Information and society. MIT Press, CambridgeCrossRef

Haider J, Sundin O (2019) Invisible search and Online search engines. Routledge, Oxford, New YorkCrossRef

White RW (2016) Interactions with search systems. Cambridge University Press, New YorkCrossRef

Järvelin K (2019) Salton award keynote. ACM SIGIR Forum 52:52–63. https://doi.org/10.1145/3308774.3308782CrossRef

Belkin NJ (2015) Salton award lecture people, interacting with information. In: SIGIR 2015—Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM Press, New York, pp 1–2

Lewandowski D (2014) Die Macht der Suchmaschinen und ihr Einfluss auf unsere Entscheidungen. Inf Wiss Prax 65:231–238. https://doi.org/10.1515/iwp-2014-0050CrossRef

Lewandowski D, Kerkmann F, Sünkler S (2014) Wie Nutzer im Suchprozess gelenkt werden: Zwischen technischer Unterstützung und interessengeleiteter Darstellung. In: Stark B, Dörr D, Aufenanger S (eds) Die Googleisierung der Informationssuche – Suchmaschinen im Spannungsfeld zwischen Nutzung und Regulierung. De Gruyter, Berlin

Lewandowski D, Kammerer Y (2020) Factors influencing viewing behaviour on search engine results pages: a review of eye-tracking research. Behav Inf Technol. https://doi.org/10.1080/0144929X.2020.1761450CrossRef

Lewandowski D, Kerkmann F, Rümmele S, Sünkler S (2018) An empirical investigation on search engine ad disclosure. J Assoc Inf Sci Technol 69:420–437. https://doi.org/10.1002/asi.23963CrossRef

10.

Schultheiß S, Lewandowski D (2021) Misplaced trust? The relationship between trust, ability to identify commercially influenced results, and search engine preference. J Inf Sci. https://doi.org/10.1177/01655515211014157CrossRef

11.

European Commission (2016) Special eurobarometer 447—Online platforms. European Commission, Brussels https://doi.org/10.2759/937517CrossRef

12.

Lewandowski D (2018) Suchmaschinen verstehen, 2nd edn. Springer, Berlin, Heidelberg, New YorkCrossRef

13.

Manning CD, Raghavan P, Schütze H (2008) Introduction to information retrieval. Cambridge University Press, CambridgeCrossRef

14.

Croft WB, Metzler D, Strohman T (2009) Search engines: information retrieval in practice. Pearson, Boston

15.

Büttcher S, Clarke CLA (2010) Information retrieval: implementing and evaluating search engines. MIT Press, CambridgeMATH

16.

Lewandowski D (2017) Users’ understanding of search engine advertisements. J Inf Sci Theory Pract 5:6–25. https://doi.org/10.1633/JISTaP.2017.5.4.1CrossRef

17.

Schultheiß S, Lewandowski D (2021) How users’ knowledge of advertisements influences their viewing and selection behavior in search engines. J Assoc Inf Sci Technol. https://doi.org/10.1002/asi.24410CrossRef

18.

Li K, Lin M, Lin Z, Xing B (2014) Running and chasing—The competition between paid search marketing and search engine optimization. In: Proc Annu Hawaii Int Conf Syst Sci, pp 3110–3119 https://doi.org/10.1109/HICSS.2014.640CrossRef

19.

Schultheiß S, Lewandowski D (2021) Expert interviews with stakeholder groups in the context of commercial search engines within the SEO effect project. https://osf.io/5aufr/. Accessed: 9 June 2021

20.

Schultheiß S, Lewandowski D (2020) “Outside the industry, nobody knows what we do” SEO as seen by search engine optimizers and content providers. J Doc 77:542–557. https://doi.org/10.1108/JD-07-2020-0127CrossRef

21.

McCue T (2018) SEO industry approaching $80 billion but all you want is more web traffic. In: forbes.com. https://www.forbes.com/sites/tjmccue/2018/07/30/seo-industry-approaching-80-billion-but-all-you-want-is-more-web-traffic/. Accessed: 9 June 2021

22.

Erlhofer S (2020) Suchmaschinen-Optimierung: das umfassende Handbuch, 10th edn. Rheinwerk Computing, Bonn

23.

Enge E, Spencer S, Stricchiola J (2015) The Art of SEO: mastering search engine optimization, 3rd edn. O’Reilly, Sebastopol

24.

Petrescu P (2014) Google organic click-through rates in 2014. https://moz.com/blog/google-organic-click-through-rates-in-2014. Accessed: 9 June 2021

25.

Goel S, Broder A, Gabrilovich E, Pang B (2010) Anatomy of the long tail. In: Davison BD, Suel T, Craswell N, Liu B (eds) Proceedings of the third ACM international conference on Web search and data mining—WSDM ’10. ACM Press, New York, p 201CrossRef

26.

Lewandowski D, Sünkler S, Yagci N (2021) The influence of search engine optimization on Google’s results: a multi-dimensional approach for detecting SEO. In: WebSci ’21: Proceedings of the 13th ACM Conference on Web Science. ACM, New York https://doi.org/10.1145/3447535.3462479CrossRef

27.

Beel J, Gipp B, Wilde E (2010) Academic search engine optimization (ASEO/span). J Sch Publ 41:176–190. https://doi.org/10.3138/jsp.41.2.176CrossRef

28.

Lewandowski D, Sünkler S (2013) Representative online study to evaluate the commitments proposed by Google as part of EU competition investigation AT. 39740-Google: report for Germany. https://searchstudies.org/wp-content/uploads/2021/06/Google_Online_Survey_DE.pdf. Accessed: 9 June 2021

29.

Schultheiß S, Linhart A, Behnert C et al (2020) Known-item searches and search tactics in library search systems: results from four transaction log analysis studies. J Acad Librariansh 46:102202. https://doi.org/10.1016/j.acalib.2020.102202CrossRef

30.

Behnert C, Lewandowski D (2017) Known-item searches resulting in zero hits: considerations for discovery systems. J Acad Librariansh 43:128–134. https://doi.org/10.1016/j.acalib.2016.12.002CrossRef

31.

Sanderson M, Croft WB (2012) The history of information retrieval research. Proc IEEE 100:1444–1451. https://doi.org/10.1109/JPROC.2012.2189916CrossRef

32.

Stock WG, Stock M (2013) Handbook of information science. De Gruyter, BerlinCrossRef

33.

Lewandowski D (2018) Zugänglichkeit von Information Services und ihren Inhalten über Suchmaschinen. In: Schade F, Georgy U (eds) Praxishandbuch Informationsmarketing. De Gruyter, Berlin, Boston, pp 358–369CrossRef

34.

Behnert C (2019) Investigating the effects of popularity data on predictive relevance judgments in academic search systems. In: Proceedings of the 2019 Conference on Human Information Interaction and Retrieval. ACM, New York, pp 437–440CrossRef

35.

Behnert C (2019) Kriterien und Einflussfaktoren bei der Relevanzbewertung von Surrogaten in akademischen Informationssystemen. Inf Wiss Prax 70:24–32

36.

Singer G, Norbisrath U, Vainikko E et al (2011) Search-logger analyzing exploratory search tasks. In: Proceedings of the 2011 ACM Symposium on Applied Computing—SAC ’11. ACM Press, New York, pp 751–756CrossRef

37.

Sünkler S, Lewandowski D (2017) Does it matter which search engine is used? A user study using post-task relevance judgments. Proc Assoc Inf Sci Technol 54:405–414. https://doi.org/10.1002/pra2.2017.14505401044CrossRef

38.

Lewandowski D (2019) The web is missing an essential part of infrastructure: an open web index. Commun ACM 62:24–27. https://doi.org/10.1145/3312479CrossRef

39.

Lewandowski D (2016) Perspektiven eines Open Web Index. Inf Wiss Prax 67:15–21. https://doi.org/10.1515/iwp-2016-0020CrossRef

40.

Lewandowski D (2014) Why we need an independent index of the web. In: König R, Rasch M (eds) Society of the query reader: reflections on web search. Institute of Network Culture, Amsterdam, pp 49–58

41.

Blank D, Fuhr N, Henrich A, Mandl T, Rölleke T, Schütze H, Stein B (2011) Teaching IR: curricular considerations. In: Efthimiadis E (ed) Teaching and learning in information retrieval. Springer, Berlin, Heidelberg, New York, pp 31–46 https://doi.org/10.1007/978-3-642-22511-6_3CrossRef

42.

Markov I, de Rijke M (2019) What should we teach in information retrieval? ACM SIGIR Forum 52:19–39. https://doi.org/10.1145/3308774.3308780CrossRef

43.

Lewandowski D, Sünkler S, Schultheiß S (2020) Studies on search: designing meaningful IIR studies on commercial search engines. Datenbank Spektrum 20:5–15. https://doi.org/10.1007/s13222-020-00331-1CrossRef

Title: The Search Studies Group at Hamburg University of Applied Sciences
Authors: Dirk Lewandowski
Sebastian Sünkler
Sebastian Schultheiß
Helena Häußler
Ulrike Spree
Christiane Behnert
Publication date: 22-06-2021
Publisher: Springer Berlin Heidelberg
Published in: Datenbank-Spektrum / Issue 2/2021
Print ISSN: 1618-2162
Electronic ISSN: 1610-1995
DOI: https://doi.org/10.1007/s13222-021-00375-x

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Datenbank-Spektrum

Other articles of this Issue 2/2021

Editorial

SQLValidator – An Online Student Playground to Learn SQL

One DB Does Not Fit It All: Teaching the Differences in Advanced Database Systems

ALEA – Adaptive eLEArning System – Lernende datenbankbasierte Lernsysteme in der Datenbanklehre

Es EILD – Anforderungen an die Publikation freier Lerneinheiten (OER) im Fach Datenbanken

News

Premium Partner