LEADER 06116nam 2200517 450 001 996547955503316 005 20230515153444.0 010 $a9783031232299$b(electronic bk.) 010 $z9783031232282 024 7 $a10.1007/978-3-031-23229-9 035 $a(MiAaPQ)EBC7202920 035 $a(Au-PeEL)EBL7202920 035 $a(CKB)26154737500041 035 $a(DE-He213)978-3-031-23229-9 035 $a(PPN)268204829 035 $a(EXLCZ)9926154737500041 100 $a20230515d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 12$aA Behavioral Economics Approach to Interactive Information Retrieval $eUnderstanding and Supporting Boundedly Rational Users /$fJiqun Liu 205 $a1st ed. 2023. 210 1$aCham, Switzerland :$cSpringer,$d[2023] 210 4$dİ2023 215 $a1 online resource (220 pages) 225 1 $aThe Information Retrieval Series ;$vVolume 48 311 08$aPrint version: Liu, Jiqun A Behavioral Economics Approach to Interactive Information Retrieval Cham : Springer International Publishing AG,c2023 9783031232282 320 $aIncludes bibliographical references. 327 $aIntro -- Foreword -- References -- Preface -- Contents -- Acronyms -- Part I: Foundation -- Chapter 1: Introduction -- 1.1 Background -- 1.2 Book Structure -- References -- Chapter 2: Formally Modeling Users in Information Retrieval -- 2.1 Introduction -- 2.2 Basic Click Models -- 2.3 Advanced Click Models -- 2.4 Clicks and Examinations in Multi-query Search Sessions -- 2.5 Incorporating Users into Click Models -- 2.6 User Models and IR Evaluation Metrics -- 2.7 Summary -- References -- Chapter 3: From Rational Agent to Human with Bounded Rationality -- 3.1 Background -- 3.2 Gaps Between Biased Users and Formal User Models -- 3.3 Hidden Problems Behind Metric-Bias Gaps -- 3.4 Preliminary Bias-Aware Interactive User Modeling and Evaluation Framework -- 3.5 Summary -- References -- Part II: Beyond Rational Agents -- Chapter 4: Bounded Rationality in Decision-Making Under Uncertainty -- 4.1 Background -- 4.2 Two Systems of Human Cognition: Which One Are We Using? -- 4.3 Reference Dependence -- 4.4 Loss Aversion, Endowment Effect, and Status Quo Bias -- 4.5 Expectation (Dis)confirmation Theory -- 4.6 Framing Effect, Confirmation Bias, and Anchoring Bias -- 4.7 Decoy Effect -- 4.8 Peak-End Rule, Recency Effect, and Remembered Utility -- 4.9 Other Biases and Heuristics in Decision-Making Under Uncertainty -- 4.10 Summary -- References -- Chapter 5: Back to the Fundamentals: Extend the Rational Assumptions -- 5.1 Introduction -- 5.2 Pre-search Stage -- 5.3 Within-Search Stage -- 5.4 Post-search Stage -- 5.5 Summary -- References -- Part III: Toward a Behavioral Economics Approach -- Chapter 6: Behavioral Economics in IR -- 6.1 Introduction -- 6.2 From Rational Agents to Boundedly Rational Decision Makers -- 6.3 Pre-search Stage -- 6.4 Within-Search Stage -- 6.5 Post-search Stage -- 6.6 Behavioral Economics and Recommender Systems -- 6.7 Summary. 327 $aReferences -- Chapter 7: Implications and New Directions for IR Research and Practices -- 7.1 Background -- 7.2 Characterizing Bounded Rationality in IR -- 7.3 Development of Bias-Aware Interactive Search Systems -- 7.4 Bias in Multiple Forms and Modalities of Search Interactions -- 7.5 Bias-Aware Evaluation and FATE in IR -- 7.6 Summary -- References -- Chapter 8: Conclusion -- References -- Glossary. 330 $aThis book brings together the insights from three different areas, Information Seeking and Retrieval, Cognitive Psychology, and Behavioral Economics, and shows how this new interdisciplinary approach can advance our knowledge about users interacting with diverse search systems, especially their seemingly irrational decisions and anomalies that could not be predicted by most normative models. The first part ?Foundation? of this book introduces the general notions and fundamentals of this new approach, as well as the main concepts, terminology and theories. The second part ?Beyond Rational Agents? describes the systematic biases and cognitive limits confirmed by behavioral experiments of varying types and explains in detail how they contradict the assumptions and predictions of formal models in information retrieval (IR). The third part ?Toward A Behavioral Economics Approach? first synthesizes the findings from existing preliminary research on bounded rationality and behavioral economics modeling in information seeking, retrieval, and recommender system communities. Then, it discusses the implications, open questions and methodological challenges of applying the behavioral economics framework to different sub-areas of IR research and practices, such as modeling users and search sessions, developing unbiased learning to rank and adaptive recommendations algorithms, implementing bias-aware intelligent task support, as well as extending the conceptualization and evaluation on IR fairness, accountability, transparency and ethics (FATE) with the knowledge regarding both human biases and algorithmic biases. This book introduces a behavioral economics framework to IR scientists seeking a new perspective on both fundamental and new emerging problems of IR as well as the development and evaluation of bias-aware intelligent information systems. It is especially intended for researchers working on IR and human-information interaction who want to learn about the potential offered by behavioral economics in their own research areas. 410 0$aInformation retrieval series ;$vVolume 48. 606 $aCognitive psychology 606 $aEconomics$xPsychological aspects 615 0$aCognitive psychology. 615 0$aEconomics$xPsychological aspects. 676 $a153 700 $aLiu$b Jiqun$01334143 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a996547955503316 996 $aA Behavioral Economics Approach to Interactive Information Retrieval$93044741 997 $aUNISA