Cognitive Biases in Search A Review and Reflection of Cognitive Biases in Information Retrieval

被引:107
作者
Azzopardi, Leif [1 ]
机构
[1] Univ Strathclyde, Glasgow, Lanark, Scotland
来源
CHIIR '21: PROCEEDINGS OF THE 2021 CONFERENCE ON HUMAN INFORMATION INTERACTION AND RETRIEVAL | 2021年
关键词
Cognitive Bias; Heuristics; Search; Information Retrieval; PROBABILITY RANKING PRINCIPLE; HEURISTICS; IMPROVE; GOOGLE;
D O I
10.1145/3406522.3446023
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
People are susceptible to an array of cognitive biases, which can result in systematic errors and deviations from rational decision making. Over the past decade, an increasing amount of attention has been paid towards investigating how cognitive biases influence information seeking and retrieval behaviours and outcomes. In particular, how such biases may negatively affect decisions because, for example, searchers may seek confirmatory but incorrect information or anchor on an initial search result even if its incorrect. In this perspectives paper, we aim to: (1) bring together and catalogue the emerging work on cognitive biases in the field of Information Retrieval; and (2) provide a critical review and reflection on these studies and subsequent findings. During our analysis we report on over thirty studies, that empirically examined cognitive biases in search, providing over forty key findings related to different domains (e.g. health, web, socio-political) and different parts of the search process (e.g. querying, assessing, judging, etc.). Our reflection highlights the importance of this research area, and critically discusses the limitations, difficulties and challenges when investigating this phenomena along with presenting open questions and future directions in researching the impact - both positive and negative - of cognitive biases in Information Retrieval.
引用
收藏
页码:27 / 37
页数:11
相关论文
共 87 条
[1]  
Abualsaud Mustafa, 2019, ROME 2019 WORKSH RED
[2]   A Review of Factors Influencing User Satisfaction in Information Retrieval [J].
Al-Maskari, Azzah ;
Sanderson, Mark .
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 2010, 61 (05) :859-868
[3]  
[Anonymous], 2012, P 5 ACM INT C WEB SE
[4]  
[Anonymous], 1988, J Behav Decis Mak, DOI [10.1002/bdm.3960010303, DOI 10.1002/BDM.3960010303]
[5]  
Azzopardi Leif, 2016, Advances in Information Retrieval. 38th European Conference on IR Research, ECIR 2016. Proceedings
[6]  
LNCS 9626, P696, DOI 10.1007/978-3-319-30671-1_55
[7]  
Azzopardi L., 2008, CIKM, P561, DOI [10.1145/1458082.1458157, DOI 10.1145/1458082.1458157]
[8]   Modelling Interaction with Economic Models of Search [J].
Azzopardi, Leif .
SIGIR'14: PROCEEDINGS OF THE 37TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, 2014, :3-12
[9]  
Azzopardi L, 2011, PROCEEDINGS OF THE 34TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR'11), P15
[10]   Bias on the Web [J].
Baeza-Yates, Ricardo .
COMMUNICATIONS OF THE ACM, 2018, 61 (06) :54-61