Evaluation Metrics for Measuring Bias in Search Engine Results
Gizem Gezici, Aldo Lipani, Yucel Saygin, and Emine Yilmaz

TL;DR
This paper introduces new metrics and a framework to evaluate bias in search engine results, focusing on stance and ideological bias across controversial topics, revealing that search engines exhibit ideological bias but not stance bias.
Contribution
The work proposes novel bias evaluation measures and a framework for analyzing search engine bias, applied to real-world search engines on controversial topics.
Findings
Search engines do not exhibit stance bias.
Both search engines show significant ideological bias.
Bias contributes to societal polarization.
Abstract
Search engines decide what we see for a given search query. Since many people are exposed to information through search engines, it is fair to expect that search engines are neutral. However, search engine results do not necessarily cover all the viewpoints of a search query topic, and they can be biased towards a specific view since search engine results are returned based on relevance, which is calculated using many features and sophisticated algorithms where search neutrality is not necessarily the focal point. Therefore, it is important to evaluate the search engine results with respect to bias. In this work we propose novel web search bias evaluation measures which take into account the rank and relevance. We also propose a framework to evaluate web search bias using the proposed measures and test our framework on two popular search engines based on 57 controversial query topics…
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Taxonomy
TopicsAdvanced Text Analysis Techniques · Sentiment Analysis and Opinion Mining · Text and Document Classification Technologies
MethodsTest
