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Do users trust search engines? And if so, why?: Developing a trust measure and applying it in an experiment

Published:20 March 2023Publication History

ABSTRACT

Nowadays, users trusting search engines seems a matter of course. However, in the face of critical evaluation of information, the apparent authority of search engines should be investigated. Therefore, the question arises again as to what extent users trust search engines and what their reasons for trusting them are. It is vital to untangle trust, trustworthiness, and trust-related behavior to address this question, a shortcoming of previous studies. The clarification helps to find evidence on the causes and effects of trust. Since there is not an adequate trust measure for technical artifacts to date, it will be developed with the help of a controlled laboratory study and validated with an online questionnaire. The measure will be applied in an online experiment to scenarios from the health and finance domain and the search engines Google and Ecosia. The expected results determine misplaced and legitimate trust in search engines. Consequently, this furthers the discussion among civil society, researchers, and policymakers on the societal consequences of trust, the role of search engines, and the necessary user skills. Additionally, the developed trust measure may be applied to novel AI applications.

References

  1. Cecilia Andersson. 2017. “Google is not fun”: an investigation of how Swedish teenagers frame online searching. Journal of Documentation 73, 6 (2017), 1244–1260. DOI:https://doi.org/10.1108/JD-03-2017-0048Google ScholarGoogle ScholarCross RefCross Ref
  2. Patricia Beatty, Ian Reay, Scott Dick, and James Miller. 2011. Consumer trust in e-commerce web sites. ACM Computing Surveys 43, 3 (2011), 1–46. DOI:https://doi.org/10.1145/1922649.1922651Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Edelman (Ed.). 2022. Edelman Trust Barometer 2022: Global Report. Retrieved from https://www.edelman.com/sites/g/files/aatuss191/files/2022-01/2022%20Edelman%20Trust%20Barometer%20FINAL_Jan25.pdfGoogle ScholarGoogle Scholar
  4. David B. Flora. 2018. Statistical methods for the social & behavioural sciences: a model-based approach. SAGE, Los Angeles ; London.Google ScholarGoogle Scholar
  5. Nicole Gillespie. 2015. Survey measures of trust in organizational contexts: an overview. In Handbook of Research Methods on Trust, Fergus Lyon, Guido Möllering and Mark N.K. Saunders (eds.). Edward Elgar Publishing, Cheltenham, 225–239.Google ScholarGoogle Scholar
  6. Ella Glikson and Anita Williams Woolley. 2020. Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals 14, 2 (2020), 627–660. DOI:https://doi.org/10.5465/annals.2018.0057Google ScholarGoogle ScholarCross RefCross Ref
  7. Jutta Haider and Olof Sundin. 2022. Paradoxes of Media and Information Literacy: The Crisis of Information. Routledge, London.Google ScholarGoogle Scholar
  8. Joseph A. Hamm and Lesa Hoffman. 2016. Working with Covariance: Using Higher-Order Factors in Structural Equation Modeling with Trust Constructs. In Interdisciplinary Perspectives on Trust, Ellie Shockley, Tess M.S. Neal, Lisa M. PytlikZillig and Brian H. Bornstein (eds.). Springer, Cham, 85–97.Google ScholarGoogle Scholar
  9. E. Hargittai, Lindsay Fullerton, Ericka Menchen-Trevino, and Kristin Yates Thomas. 2010. Trust Online: Young Adults’ Evaluation of Web Content. International Journal of Communication 4, (2010), 468–494.Google ScholarGoogle Scholar
  10. Diane Kelly. 2009. Methods for Evaluating Interactive Information Retrieval Systems with Users. Now Publishers, Amsterdam. DOI:https://doi.org/10.1561/1500000012Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Jeonghyun Kim. 2009. Describing and predicting information-seeking behavior on the Web. Journal of the American Society for Information Science and Technology 60, 4 (2009), 679–693. DOI:https://doi.org/10.1002/asi.21035Google ScholarGoogle ScholarCross RefCross Ref
  12. Spencer C. Kohn, Ewart J. de Visser, Eva Wiese, Yi-Ching Lee, and Tyler H. Shaw. 2021. Measurement of Trust in Automation: A Narrative Review and Reference Guide. Frontiers in psychology 12, (2021), 604977. DOI:https://doi.org/10.3389/fpsyg.2021.604977Google ScholarGoogle ScholarCross RefCross Ref
  13. Matthias Kohring. 2004. Vertrauen in Journalismus: Theorie und Empirie. UVK, Konstanz.Google ScholarGoogle Scholar
  14. Jingjing Liu and Xiangmin Zhang. 2019. The role of domain knowledge in document selection from search results. Journal of the Association for Information Science and Technology 70, 11 (2019), 1236–1247. DOI:https://doi.org/10.1002/asi.24199Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Yan Lu, Michael Chau, and Patrick Y. K. Chau. 2017. Are Sponsored Links Effective? Investigating the Impact of Trust in Search Engine Advertising. ACM Transactions on Management Information Systems 7, 4 (2017), 1–33. DOI:https://doi.org/10.1145/3023365Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Niklas Luhmann. 2014. Vertrauen: Ein Mechanismus der Reduktion sozialer Komplexität (5. Aufl. ed.). UVK and UTB, Konstanz and Stuttgart.Google ScholarGoogle ScholarCross RefCross Ref
  17. Mykola Makhortykh, Aleksandra Urman, and Roberto Ulloa. 2020. How search engines disseminate information about COVID-19 and why they should do better. Harvard Kennedy School Misinformation Review (2020). DOI:https://doi.org/10.37016/mr-2020-017Google ScholarGoogle ScholarCross RefCross Ref
  18. Roger C. Mayer, James H. Davis, and F. David Schoorman. 1995. An Integrative Model of Organizational Trust. Academy of Management Review 20, 3 (1995), 709–734.Google ScholarGoogle ScholarCross RefCross Ref
  19. Philipp Mayring. 2014. Qualitative content analysis: theoretical foundation, basic procedures and software solution. Klagenfurt. Retrieved from https://nbn-resolving.org/urn:nbn:de:0168-ssoar-395173Google ScholarGoogle Scholar
  20. Bill McEvily and Marco Tortoriello. 2011. Measuring trust in organisational research: Review and recommendations. Journal of Trust Research 1, 1 (2011), 23–63. DOI:https://doi.org/10.1080/21515581.2011.552424Google ScholarGoogle ScholarCross RefCross Ref
  21. D. Harrison McKnight and Norman L. Chervany. 2001. Trust and Distrust Definitions: One Bite at a Time. In Trust in cyber-societies, Rino Falcone, Munindar P. Singh and Yao-Hua Tan (eds.). Springer, Berlin and New York, 27–54.Google ScholarGoogle Scholar
  22. Peter Nannestad. 2008. What Have We Learned About Generalized Trust, If Anything? Annual Review of Political Science 11, 1 (2008), 413–436. DOI:https://doi.org/10.1146/annurev.polisci.11.060606.135412Google ScholarGoogle ScholarCross RefCross Ref
  23. Pandu Nayak. 2021. MUM: A new AI milestone for understanding information. The Keyword. Retrieved from https://blog.google/products/search/introducing-mum/Google ScholarGoogle Scholar
  24. Bing Pan, Helene Hembrooke, Thorsten Joachims, Lori Lorigo, Geri Gay, and Laura Granka. 2007. In Google we trust: Users’ decisions on rank, position, and relevance. Journal of Computer-Mediated Communication 12, 3 (2007). DOI:https://doi.org/10.1111/j.1083-6101.2007.00351.xGoogle ScholarGoogle ScholarCross RefCross Ref
  25. Lisa M. PytlikZillig and Christopher D. Kimbrough. 2016. Consensus on Conceptualizations and Definitions of Trust: Are We There Yet? In Interdisciplinary Perspectives on Trust, Ellie Shockley, Tess M.S. Neal, Lisa M. PytlikZillig and Brian H. Bornstein (eds.). Springer, Cham, 17–47.Google ScholarGoogle Scholar
  26. Oya Y. Rieger. 2009. Search engine use behavior of students and faculty: User perceptions and implications for future research. First Monday 14, 12 (2009). DOI:https://doi.org/10.5210/fm.v14i12.2716Google ScholarGoogle ScholarCross RefCross Ref
  27. Sebastian Schultheiß and Dirk Lewandowski. 2021. A representative online survey among German search engine users with a focus on questions regarding search engine optimization (SEO): a study within the SEO Effect project. Retrieved from https://osf.io/wzhxsGoogle ScholarGoogle Scholar
  28. Sebastian Schultheiß, Sebastian Sünkler, and Dirk Lewandowski. 2018. We still trust in Google, but less than 10 years ago: an eye-tracking study. Information Research 23, 3 (2018). Retrieved from http://www.informationr.net/ir/23-3/paper799.htmlGoogle ScholarGoogle Scholar
  29. Jason Bennett Thatcher, D. Harrison McKnight, Elizabeth White Baker, Riza Ergun Arsal, and Nicholas H. Roberts. 2011. The Role of Trust in Postadoption IT Exploration: An Empirical Examination of Knowledge Management Systems. IEEE Transactions on Engineering Management 58, 1 (2011), 56–70. DOI:https://doi.org/10.1109/TEM.2009.2028320Google ScholarGoogle ScholarCross RefCross Ref
  30. Julian Unkel and Alexander Haas. 2017. The effects of credibility cues on the selection of search engine results. Journal of the Association for Information Science and Technology 68, 8 (2017), 1850–1862. DOI:https://doi.org/10.1002/asi.23820Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Lisa van der Werff, Colette Real, and Theodore G. Lynn. 2018. Individual Trust and the Internet. In The Routledge Companion to Trust, Rosalind Searle, Ann-Marie Ingrid Nienaber and Sim B. Sitkin (eds.). Taylor & Francis Group, Abingdon, Oxon and New York, NY, 391–407.Google ScholarGoogle Scholar
  32. Sam Wineburg and Sarah McGrew. 2019. Lateral Reading and the Nature of Expertise: Reading Less and Learning More When Evaluating Digital Information. Teachers College Record: The Voice of Scholarship in Education 121, 11 (2019), 1–40. DOI:https://doi.org/10.1177/016146811912101102Google ScholarGoogle ScholarCross RefCross Ref

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    • Published in

      cover image ACM Conferences
      CHIIR '23: Proceedings of the 2023 Conference on Human Information Interaction and Retrieval
      March 2023
      520 pages
      ISBN:9798400700354
      DOI:10.1145/3576840
      • Editors:
      • Jacek Gwizdka,
      • Soo Young Rieh

      Copyright © 2023 Owner/Author

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      • Published: 20 March 2023

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