Search Engine Similarity Analysis: A Combined Content and Rankings Approach

TL;DR

This study introduces a new similarity metric combining content and ranking to compare search engine results, revealing distinct differences between Google and the similar Bing and DuckDuckGo, and analyzing their evolution over time.

Contribution

The paper presents a novel similarity metric for search results that considers both content and ranking, and applies it to compare major search engines over time.

Findings

Google results are notably distinct from Bing and DuckDuckGo.

Bing and DuckDuckGo results are largely similar.

Search engine similarity evolves over time.

Abstract

How different are search engines? The search engine wars are a favorite topic of on-line analysts, as two of the biggest companies in the world, Google and Microsoft, battle for prevalence of the web search space. Differences in search engine popularity can be explained by their effectiveness or other factors, such as familiarity with the most popular first engine, peer imitation, or force of habit. In this work we present a thorough analysis of the affinity of the two major search engines, Google and Bing, along with DuckDuckGo, which goes to great lengths to emphasize its privacy-friendly credentials. To do so, we collected search results using a comprehensive set of 300 unique queries for two time periods in 2016 and 2019, and developed a new similarity metric that leverages both the content and the ranking of search responses. We evaluated the characteristics of the metric against other metrics and approaches that have been proposed in the literature, and used it to (1) investigate the similarities of search engine results, (2) the evolution of their affinity over time, (3) what aspects of the results influence similarity, and (4) how the metric differs over different kinds of search services. We found that Google stands apart, but Bing and DuckDuckGo are largely indistinguishable from each other.