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This report aims to report my thesis progress so far. My work attempts to show the differences in the perspectives of two search engines, Bing and Google on several selected controversial topics. In this work, we try to make a distinction…

Information Retrieval · Computer Science 2022-11-22 Gizem Gezici

Search engines can be considered as a gate to the world of WEB, and they also 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 should…

Information Retrieval · Computer Science 2021-12-28 Gizem Gezici

Finding a product online can be a challenging task for users. Faceted search interfaces, often in combination with recommenders, can support users in finding a product that fits their preferences. However, those preferences are not always…

Information Retrieval · Computer Science 2023-02-14 Dagmar Kern , Wilko van Hoek , Daniel Hienert

Major search engines deploy personalized Web results to enhance users' experience, by showing them data supposed to be relevant to their interests. Even if this process may bring benefits to users while browsing, it also raises concerns on…

Information Retrieval · Computer Science 2015-08-18 Van Tien Hoang , Angelo Spognardi , Francesco Tiezzi , Marinella Petrocchi , Rocco De Nicola

In this work, we aim to investigate the impact of location (different countries) on bias in search results. For this, we use the search results of Google and Bing in the UK and US locations. The query set is composed of controversial…

Information Retrieval · Computer Science 2022-06-24 Gizem Gezici

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…

Information Retrieval · Computer Science 2023-02-07 Gizem Gezici , Aldo Lipani , Yucel Saygin , Emine Yilmaz

There is a growing demand for transparency in search engines to understand how search results are curated and to enhance users' trust. Prior research has introduced search result explanations with a focus on how to explain, assuming…

Human-Computer Interaction · Computer Science 2024-02-26 Prerna Juneja , Wenjuan Zhang , Alison Marie Smith-Renner , Hemank Lamba , Joel Tetreault , Alex Jaimes

The objective of this research was to find out how the two search engines Google and Bing perform when users work freely on pre-defined tasks, and judge the relevance of the results immediately after finishing their search session. In a…

Human-Computer Interaction · Computer Science 2017-10-24 Sebastian Suenkler , Dirk Lewandowski

When interacting with information retrieval (IR) systems, users, affected by confirmation biases, tend to select search results that confirm their existing beliefs on socially significant contentious issues. To understand the judgments and…

Information Retrieval · Computer Science 2024-06-18 Ben Wang , Jiqun Liu

Web search is an integral part of our daily lives. Recently, there has been a trend of personalization in Web search, where different users receive different results for the same search query. The increasing level of personalization is…

Computers and Society · Computer Science 2017-06-19 Anikó Hannák , Piotr Sapieżyński , Arash Molavi Khaki , David Lazer , Alan Mislove , Christo Wilson

Conflicts of interest often arise between data sources and their users regarding how the users' information needs should be interpreted by the data source. For example, an online product search might be biased towards presenting certain…

Databases · Computer Science 2026-03-09 Nischal Aryal , Arash Termehchy , Marianne Winslett

The way pages are ranked in search results influences whether the users of search engines are exposed to more homogeneous, or rather to more diverse viewpoints. However, this viewpoint diversity is not trivial to assess. In this paper we…

Information Retrieval · Computer Science 2021-07-06 Tim Draws , Nava Tintarev , Ujwal Gadiraju , Alessandro Bozzon , Benjamin Timmermans

People use web search engines to find information before forming opinions, which can lead to practical decisions with different levels of impact. The cognitive effort of search can leave opinionated users vulnerable to cognitive biases,…

Information Retrieval · Computer Science 2023-09-18 Z. Wu , T. Draws , F. Cau , F. Barile , A. Rieger , N. Tintarev

Search query suggestions affect users' interactions with search engines, which then influences the information they encounter. Thus, bias in search query suggestions can lead to exposure to biased search results and can impact opinion…

Information Retrieval · Computer Science 2024-11-01 Fabian Haak , Björn Engelmann , Christin Katharina Kreutz , Philipp Schaer

Internet users highly rely on and trust web search engines, such as Google, to find relevant information online. However, scholars have documented numerous biases and inaccuracies in search outputs. To improve the quality of search results,…

Computers and Society · Computer Science 2023-10-06 Aleksandra Urman , Aniko Hannak , Mykola Makhortykh

Search engines have become key media for our scientific, economic, and social activities by enabling people to access information on the Web in spite of its size and complexity. On the down side, search engines bias the traffic of users…

Computers and Society · Computer Science 2009-02-19 Santo Fortunato , Alessandro Flammini , Filippo Menczer , Alessandro Vespignani

Information availability affects people's behavior and perception of the world. Notably, people rely on search engines to satisfy their need for information. Search engines deliver results relevant to user requests usually without being or…

Information Retrieval · Computer Science 2021-10-19 Aldo Lipani , Florina Piroi , Emine Yilmaz

Click-through data has proven to be a valuable resource for improving search-ranking quality. Search engines can easily collect click data, but biases introduced in the data can make it difficult to use the data effectively. In order to…

Machine Learning · Computer Science 2020-02-13 Yingcheng Sun , Richard Kolacinski , Kenneth Loparo

Different search engines provide different outputs for the same keyword. This may be due to different definitions of relevance, and/or to different knowledge/anticipation of users' preferences, but rankings are also suspected to be biased…

Information Retrieval · Computer Science 2018-08-06 Ahmed Kamoun , Patrick Maillé , Bruno Tuffin

Researchers rely on academic Web search engines to find scientific sources, but search engine mechanisms may selectively present content that aligns with biases embedded in queries. This study examines whether confirmation biased queries…

Computers and Society · Computer Science 2025-01-03 Celina Kacperski , Mona Bielig , Mykola Makhortykh , Maryna Sydorova , Roberto Ulloa
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