A Comparison of Source Distribution and Result Overlap in Web Search Engines

S. Geiss Birgit Stark M. Steiner + 1 lainnya

24 Juni 2020

ABSTRACT Search engines are important political news sources and should thus provide users with diverse political information – an important precondition of a well-informed citizenry. The search engines’ algorithmic content selection strongly influences the diversity of the content received by the users – particularly since most users highly trust search engines and often click on only the first result. A widespread concern is that users are not informed diversely by search engines, but how far this concern applies has hardly been investigated. Our study is the first to investigate content diversity provided by five search engines on ten current political issues in Germany. The findings show that sometimes even the first result is highly diverse, but in most cases, more results must be considered to be informed diversely. This unreliability presents a serious challenge when using search engines as political news sources. Our findings call for media policy measures, for example in terms of algorithmic transparency.

Sebastian Schultheiß D. Lewandowski

12 September 2022

To gain a better understanding of user knowledge and perspectives of search engines, a fruitful approach are representative online surveys. In 2020, we conducted an online survey with a sample representative of the German online population aged 16 through 69 ( N = 2,012). The online survey included 12 search engine-related sections. The questions cover topics such as usage behavior, self-assessed search engine literacy, trust in search engines, knowledge of ads and search engine optimization (SEO), ability to distinguish ads from organic results, assessments and opinions regarding SEO, and personalization of search results. SEO is the specific focus of the survey, as it was conducted as part of the SEO Effect project, dealing with issues such as the role of SEO from the user perspective. This data set contains complete data from the online survey. On the one hand, the data set will allow further analyses, and, on the other hand, comparisons with follow-up studies.

O. Sundin Jutta Haider D. Lewandowski

21 Agustus 2021

This opinion piece takes Google's response to the so‐called COVID‐19 infodemic, as a starting point to argue for the need to consider societal relevance as a complement to other types of relevance. The authors maintain that if information science wants to be a discipline at the forefront of research on relevance, search engines, and their use, then the information science research community needs to address itself to the challenges and conditions that commercial search engines create in. The article concludes with a tentative list of related research topics.

Sebastian Schultheiß D. Lewandowski Sebastian Sünkler

24 Januari 2020

The purpose of this paper is (1) to show which topics are especially fruitful for researchers interested in user behavior in commercial search engines, (2) to help researchers decide which data to collect and to what extent. We classify potential areas for IIR research along two dimensions, namely the type of interaction data used (small-scale or large-scale), and whether search engine companies are likely to publish research on the topic chosen (likely or unlikely). This results in a framework consisting of five areas, which are further detailed. In the second part of the paper, we present some empirical studies showing how researchers could approach relevant topics where no results from the search engine providers themselves are published. We also show how researchers can improve the evidential value of their work by going from small-scale to at least medium-scale studies.

Nicholas Vincent Brent J. Hecht

21 April 2020

A growing body of work has highlighted the important role that Wikipedia's volunteer-created content plays in helping search engines achieve their core goal of addressing the information needs of millions of people. In this paper, we report the results of an investigation into the incidence of Wikipedia links in search engine results pages (SERPs). Our results extend prior work by considering three U.S. search engines, simulating both mobile and desktop devices, and using a spatial analysis approach designed to study modern SERPs that are no longer just "ten blue links". We find that Wikipedia links are extremely common in important search contexts, appearing in 67-84% of all SERPs for common and trending queries, but less often for medical queries. Furthermore, we observe that Wikipedia links often appear in "Knowledge Panel" SERP elements and are in positions visible to users without scrolling, although Wikipedia appears less in prominent positions on mobile devices. Our findings reinforce the complementary notions that (1) Wikipedia content and research has major impact outside of the Wikipedia domain and (2) powerful technologies like search engines are highly reliant on free content created by volunteers.