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Lewandowski, D.: Alles nur noch Google? : Entwicklungen im Bereich der WWW-Suchmaschinen (2002)
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- Date
- 29. 9.2002 18:49:22
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Lewandowski, D.: Abfragesprachen und erweiterte Funktionen von WWW-Suchmaschinen (2004)
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- Date
- 28.11.2004 13:11:22
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Lewandowski, D.: Query understanding (2011)
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- Date
- 18. 9.2018 18:22:18
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Lewandowski, D.: ¬Die Macht der Suchmaschinen und ihr Einfluss auf unsere Entscheidungen (2014)
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- Date
- 22. 9.2014 18:54:11
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Lewandowski, D.; Sünkler, S.; Kerkmann, F.: Are ads on Google search engine results pages labeled clearly enough? : the influence of knowledge on search ads on users' selection behaviour (2017)
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- Abstract
- In an online experiment using a representative sample of the German online population (n = 1.000), we compare users' selection behaviour on two versions of the same Google search engine results page (SERP), one showing advertisements and organic results, the other showing organic results only. Selection behaviour is analyzed in relation to users' knowledge on Google's business model, on SERP design, and on these users' actual performance in marking advertisements on SERPs correctly. We find that users who were not able to mark ads correctly selected ads significantly more often. This leads to the conclusion that ads need to be labeled more clearly, and that there is a need for more information literacy in search engine users.
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Lewandowski, D.; Spree, U.: Ranking of Wikipedia articles in search engines revisited : fair ranking for reasonable quality? (2011)
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- Date
- 30. 9.2012 19:27:22
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Lewandowski, D.; Sünkler, S.: What does Google recommend when you want to compare insurance offerings? (2019)
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- Date
- 20. 1.2015 18:30:22
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Lewandowski, D.: Mit welchen Kennzahlen lässt sich die Qualität von Suchmaschinen messen? (2007)
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- Abstract
- Suchmaschinen bilden den bedeutendsten Zugang zu den im World Wide Web verfügbaren Informationen und haben andere Zugänge zu diesem Informationsbestand (wie etwa Internetverzeichnisse) weitgehend verdrängt. Der Suchmaschinenmarkt ist stark konzentriert; nur wenige Anbieter mit eigener Technologie bieten selbst Endnutzerlösungen an und lizenzieren ihre Technologie an die bekannten Web-Portale wie AOL oder T-Online. Die im vorliegenden Kapitel dargestellten Kennzahlen zur Messung der Qualität von Suchmaschinen basieren einerseits auf Erkenntnissen über den State of the Art der Suchmaschinentechnologie, andererseits stehen sie im Kontext eines umfassenderen Modells der Qualitätsmessung für Web-Suchmaschinen. Die besondere Bedeutung von Erkenntnissen über die Qualität der bestehenden Suchmaschinen ergibt sich einerseits aus ihrer Bedeutung für die Weiterentwicklung der Suchmaschinentechnologie. Qualitätsuntersuchungen geben Hinweise auf die Schwachstellen der Suchmaschinen im Allgemeinen und die ihrer Ranking-Algorithmen im Besonderen. Letztere sind als zentral für die Ergebnisqualität anzusehen und bilden den >Kern< der technologischen Leistungsfähigkeit einer jeden Suchmaschine.
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Lewandowski, D.; Sünkler, S.; Hanisch, F.: Anzeigenkennzeichnung auf Suchergebnisseiten : Empirische Ergebnisse und Implikationen für die Forschung (2019)
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- Abstract
- In diesem Aufsatz stellen wir eine repräsentative Multimethodenstudie (bestehend aus Umfrage, aufgabenbasierter Nutzerstudie und OnlineExperiment) zum Wissen und Verhalten der deutschen Internetnutzer bezüglich der Anzeigen auf Google-Suchergebnisseiten vor. Die Ergebnisse zeigen, dass die überwiegende Mehrzahl der Nutzenden nicht hinreichend in der Lage ist, Werbung von organischen Ergebnissen zu unterscheiden. Die aufgabenbasierte Studie zeigt, dass lediglich 1,3 Prozent der Teilnehmenden alle Anzeigen und organischen Ergebnisse richtig markieren konnten. 9,6 Prozent haben ausschließlich korrekte Markierungen vorgenommen, dabei aber keine Vollständigkeit erreicht. Aus den Ergebnissen der Umfrage geht hervor, dass es viele Unklarheiten gibt über das Geschäftsmodell von Google und die Art und Weise, wie Suchmaschinenwerbung funktioniert. Die Ergebnisse des Online-Experiments zeigen, dass Nutzende, die die Unterscheidung zwischen Anzeigen und organischen Ergebnissen nicht verstehen, etwa doppelt so häufig auf Anzeigen klicken wie diejenigen, die diese Unterscheidung verstehen. Implikationen für die Forschung ergeben sich in den Bereichen Wiederholungsstudien bzw. Monitoring der Anzeigendarstellung, vertiefende Laborstudien, Modelle des Informationsverhaltens, Informationskompetenz und Entwicklung fairer Suchmaschinen.
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Lewandowski, D.; Drechsler, J.; Mach, S. von: Deriving query intents from web search engine queries (2012)
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- Abstract
- The purpose of this article is to test the reliability of query intents derived from queries, either by the user who entered the query or by another juror. We report the findings of three studies. First, we conducted a large-scale classification study (~50,000 queries) using a crowdsourcing approach. Next, we used clickthrough data from a search engine log and validated the judgments given by the jurors from the crowdsourcing study. Finally, we conducted an online survey on a commercial search engine's portal. Because we used the same queries for all three studies, we also were able to compare the results and the effectiveness of the different approaches. We found that neither the crowdsourcing approach, using jurors who classified queries originating from other users, nor the questionnaire approach, using searchers who were asked about their own query that they just entered into a Web search engine, led to satisfying results. This leads us to conclude that there was little understanding of the classification tasks, even though both groups of jurors were given detailed instructions. Although we used manual classification, our research also has important implications for automatic classification. We must question the success of approaches using automatic classification and comparing its performance to a baseline from human jurors.
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Behnert, C.; Lewandowski, D.: ¬A framework for designing retrieval effectiveness studies of library information systems using human relevance assessments (2017)
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- Abstract
- Purpose This paper demonstrates how to apply traditional information retrieval evaluation methods based on standards from the Text REtrieval Conference (TREC) and web search evaluation to all types of modern library information systems including online public access catalogs, discovery systems, and digital libraries that provide web search features to gather information from heterogeneous sources. Design/methodology/approach We apply conventional procedures from information retrieval evaluation to the library information system context considering the specific characteristics of modern library materials. Findings We introduce a framework consisting of five parts: (1) search queries, (2) search results, (3) assessors, (4) testing, and (5) data analysis. We show how to deal with comparability problems resulting from diverse document types, e.g., electronic articles vs. printed monographs and what issues need to be considered for retrieval tests in the library context. Practical implications The framework can be used as a guideline for conducting retrieval effectiveness studies in the library context. Originality/value Although a considerable amount of research has been done on information retrieval evaluation, and standards for conducting retrieval effectiveness studies do exist, to our knowledge this is the first attempt to provide a systematic framework for evaluating the retrieval effectiveness of twenty-first-century library information systems. We demonstrate which issues must be considered and what decisions must be made by researchers prior to a retrieval test.
