Misplaced trust? The relationship between trust, ability to identify commercially influenced results and search engine preference

Abstract

People have a high level of trust in search engines, especially Google, but only limited knowledge of them, as numerous studies have shown. This leads to the question: To what extent is this trust justified considering the lack of familiarity among users with how search engines work and the business models they are founded on? We assume that trust in Google, search engine preferences and knowledge of result types are interrelated. To examine this assumption, we conducted a representative online survey with n = 2012 German Internet users. We show that users with little search engine knowledge are more likely to trust and use Google than users with more knowledge. A contradiction revealed itself – users strongly trust Google, yet they are unable to adequately evaluate search results. For those users, this may be problematic since it can potentially affect knowledge acquisition. Consequently, there is a need to promote user information literacy to create a more solid foundation for user trust in search engines. The impact of our study lies in emphasising the need for creating appropriate training formats to promote information literacy.

Whose relevance? Web search engines as multisided relevance machines

“…All these groups need to be served by the search engine. Thus, their respective interests will also shape what search results are shown on the SERPs (Schultheiß & Lewandowski, 2021) and how relevance is constituted. In light of this, what is relevance exactly and how can we understand the relevance of search engine results concerning a public health crisis, such as COVID-19?…”

Sender vs. recipient-orientated information systems revisited

“…This may lead to difference kinds of bias in systems including sociopolitical (Diaz, 2008), gender (Martey, 2008), commercal (Lewandowski,and Sünkler, 2019), race (Noble, 2018) etc that may favour one type of content over another (the 'long tail' problem). Trust in such systems may be misplaced (Schultheiß, and Lewandowski, 2021). The implications for the generation of knowledge through access to such global information systems are profound (Hinman, 2008) as systems such as Google act as gatekeepers and shape what we know (Schroeder, 2014).…”

“…that may favor one type of content over another (the “long tail” problem). Trust in such systems may be misplaced (Schultheiß and Lewandowski, 2021). The implications for the generation of knowledge through access to such global information systems are profound (Hinman, 2008) as systems such as Google act as gatekeepers and shape what we know (Schroeder, 2014).…”

“…GDPR in the European Union (2016). Given the legislative environment, all methods used to develop the user profile, such as tracking user interactions with results lists and documents, should be made transparent to the user, thereby promoting trust (Schultheiß and Lewandowski, 2021). It is only by learning what types of data an organization holds about them that users will understand the nature and scope of their data use and get to know the possibilities for making more specific data access requests.…”

Search a Great Leveler? Ensuring More Equitable Information Acquisition

“…To address this bias, it is paramount to better understand how results pages are generated and how (plus to what extent) key stakeholder groups influence these results. There are five such groups (Schultheiß & Lewandowski, 2021); search engine providers determine ranking through algorithms, but may unfairly promote their own offerings (European Commission, 2017); content providers influence search results not only through what they produce, but also potentially by promoting their own content using search engine optimization (SEO) and paid search marketing (PSM). These, as professions in their own right, form separate groups.…”