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Search engines are used and trusted by hundreds of millions of people every day. However, the algorithms used by search engines to index, filter, and rank web content are inherently biased, and will necessarily prefer some views and…

Computers and Society · Computer Science 2025-11-03 Ronja Rönnback , Chris Emmery , Marie Šafář Postma , Filip Milde , Jan Charvát , Henry Brighton

Given a specific query case, legal case retrieval systems aim to retrieve a set of case documents relevant to the case at hand. Previous studies on user behavior analysis have shown that information retrieval (IR) systems can significantly…

Information Retrieval · Computer Science 2023-10-10 Beining Wang , Ruizhe Zhang , Yueyue Wu , Qingyao Ai , Min Zhang , Yiqun Liu

This work investigates the effect of gender-stereotypical biases in the content of retrieved results on the relevance judgement of users/annotators. In particular, since relevance in information retrieval (IR) is a multi-dimensional…

Information Retrieval · Computer Science 2022-03-04 Klara Krieg , Emilia Parada-Cabaleiro , Markus Schedl , Navid Rekabsaz

Search engines play a central role in how people gather information, but subtle cues like headline framing may influence not only what users believe but also how they search. While framing effects on judgment are well documented, their…

Computation and Language · Computer Science 2025-08-26 Amrit Poudel , Maria Milkowski , Tim Weninger

Search engines, as cognitive partners, reshape how individuals evaluate their cognitive abilities. This study examines how search tool access influences cognitive self-esteem (CSE)-users' self-perception of cognitive abilities -- through…

Human-Computer Interaction · Computer Science 2025-01-22 Mahir Akgun , Sacip Toker

Traditional machine-learned ranking systems for web search are often trained to capture stationary relevance of documents to queries, which has limited ability to track non-stationary user intention in a timely manner. In recency search,…

Information Retrieval · Computer Science 2011-03-22 Taesup Moon , Wei Chu , Lihong Li , Zhaohui Zheng , Yi Chang

This study examines the decoy effect's underexplored influence on user search interactions and methods for measuring information retrieval (IR) systems' vulnerability to this effect. It explores how decoy results alter users' interactions…

Information Retrieval · Computer Science 2025-01-17 Nuo Chen , Jiqun Liu , Hanpei Fang , Yuankai Luo , Tetsuya Sakai , Xiao-Ming Wu

The provided contents by information retrieval (IR) systems can reflect the existing societal biases and stereotypes. Such biases in retrieval results can lead to further establishing and strengthening stereotypes in society and also in the…

Information Retrieval · Computer Science 2023-01-10 Klara Krieg , Emilia Parada-Cabaleiro , Gertraud Medicus , Oleg Lesota , Markus Schedl , Navid Rekabsaz

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

Context information in search sessions has proven to be useful for capturing user search intent. Existing studies explored user behavior sequences in sessions in different ways to enhance query suggestion or document ranking. However, a…

Information Retrieval · Computer Science 2021-08-25 Yutao Zhu , Jian-Yun Nie , Zhicheng Dou , Zhengyi Ma , Xinyu Zhang , Pan Du , Xiaochen Zuo , Hao Jiang

If popular online platforms systematically expose their users to partisan and unreliable news, they could potentially contribute to societal issues like rising political polarization. This concern is central to the echo chamber and filter…

Social and Information Networks · Computer Science 2022-09-30 Ronald E. Robertson , Jon Green , Damian J. Ruck , Katherine Ognyanova , Christo Wilson , David Lazer

Most typical click models assume that the probability of a document to be examined by users only depends on position, such as PBM and UBM. It works well in various kinds of search engines. However, in a search engine where massive candidate…

Artificial Intelligence · Computer Science 2021-01-08 Ningxin Xu , Cheng Yang , Yixin Zhu , Xiaowei Hu , Changhu Wang

Information Retrieval (IR) systems are designed to deliver relevant content, but traditional systems may not optimize rankings for fairness, neutrality, or the balance of ideas. Consequently, IR can often introduce indexical biases, or…

Information Retrieval · Computer Science 2024-06-07 Caleb Ziems , William Held , Jane Dwivedi-Yu , Diyi Yang

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

Many real-world decisions rely on information search, where people sample evidence and decide when to stop under uncertainty. The uncertainty in the environment, particularly how diagnostic evidence is distributed, causes complexities in…

Human-Computer Interaction · Computer Science 2026-02-17 Kexin Quan , Jessie Chin

Online comments significantly influence users' judgments, yet their presentation, often determined by platform algorithms, can introduce biases, such as anchoring effects, which distort reasoning. While existing research emphasizes…

Human-Computer Interaction · Computer Science 2026-01-28 Yang Ouyang , Shenghan Gao , Ruichuan Wang , Hailiang Zhu , Yuheng Shao , Xiaoyu Gu , Quan Li

People use search engines to find answers to questions related to their health, finances, or other socially relevant issues. However, most users are unaware that search results are considerably influenced by search engine marketing (SEM).…

Information Retrieval · Computer Science 2023-01-25 Sebastian Schultheiß

In the digital environment, human attention is frequently guided by cognitive heuristics rather than deliberate evaluation. Since low-credibility narratives often lack substantive factual evidence, their diffusion disproportionally relies…

Social and Information Networks · Computer Science 2026-05-07 Lynnette Hui Xian Ng , Wenqi Zhou , Kathleen M. Carley

The development of an automatic way to extract user opinions about products, movies, and foods from online social network (OSN) interactions is among the main interests of sentiment analysis and opinion mining studies. Existing approaches…

Social and Information Networks · Computer Science 2021-05-14 Amin Mahmoudi

The Web is an important resource for understanding and diagnosing medical conditions. Based on exposure to online content, people may develop undue health concerns, believing that common and benign symptoms are explained by serious…

Information Retrieval · Computer Science 2017-12-12 George Philipp , Ryen W. White