Understanding users' dynamic perceptions of search gain and cost in sessions (2024)

Abdi, H., & Williams, L. J. (2010). Tukey's honestly significant difference (HSD) test. Encyclopedia of Research Design, 3(1), 1–5.

Abeler, J., Falk, A., Goette, L., & Huffman, D. (2011). Reference points and effort provision. American Economic Review, 101(2), 470–492.

Al‐Maskari, A., & Sanderson, M. (2010). A review of factors influencing user satisfaction in information retrieval. Journal of the American Society for Information Science and Technology, 61(5), 859–868.

Azzopardi, L. (2011). The economics in interactive information retrieval. In Proceedings of the 34th international ACM SIGIR conference on research and development in information retrieval (pp. 15–24). ACM.

Azzopardi, L. (2014). Modelling interaction with economic models of search. In Proceedings of the 37th international ACM SIGIR conference on research & development in information retrieval (pp. 3–12). ACM.

Azzopardi, L. (2021). Cognitive biases in search: A review and reflection of cognitive biases in information retrieval. In Proceedings of the 2021 conference on human information interaction and retrieval (pp. 27–37). ACM.

Azzopardi, L., Kelly, D., & Brennan, K. (2013). How query cost affects search behavior. In Proceedings of the 36th international ACM SIGIR conference on research and development in information retrieval (pp. 23–32). ACM.

Azzopardi, L., Thomas, P., & Craswell, N. (2018). Measuring the utility of search engine result pages: An information foraging based measure. In The 41st international ACM SIGIR conference on research & development in information retrieval (pp. 605–614). ACM.

Azzopardi, L., & Zuccon, G. (2016). An analysis of the cost and benefit of search interactions. In Proceedings of the 2016 ACM international conference on the theory of information retrieval (pp. 59–68). ACM.

Azzopardi, L., & Zuccon, G. (2019). Building economic models of human computer interaction. In Extended abstracts of the 2019 CHI conference on human factors in computing systems (pp. 1–4). ACM.

Backus, M., Blake, T., Masterov, D., & Tadelis, S. (2022). Expectation, disappointment, and exit: Evidence on reference point formation from an online marketplace. Journal of the European Economic Association, 20(1), 116–149.

Bates, M. J. (1989). The design of browsing and berrypicking techniques for the online search interface. Online Review, 13(5), 407–424.

Berget, G., & MacFarlane, A. (2020). What is known about the impact of impairments on information seeking and searching? Journal of the Association for Information Science and Technology, 71(5), 596–611.

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation‐confirmation model. MIS Quarterly, 325, 351–370.

Cancho, R. F. I., & Solé, R. V. (2003). Least effort and the origins of scaling in human language. Proceedings of the National Academy of Sciences, 100(3), 788–791.

Chapelle, O., Metlzer, D., Zhang, Y., & Grinspan, P. (2009). Expected reciprocal rank for graded relevance. In Proceedings of the 18th ACM conference on information and knowledge management (pp. 621–630). ACM.

Chen, N., Liu, J., & Sakai, T. (2023). A reference‐dependent model for web search evaluation: Understanding and measuring the experience of boundedly rational users. In Proceedings of the ACM web conference 2023 (pp. 3396–3405). ACM.

Chen, N., Zhang, F., & Sakai, T. (2022). Constructing better evaluation metrics by incorporating the anchoring effect into the user model. In Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval. ACM.

Chen, S.‐C., Yen, D. C., & Hwang, M. I. (2012). Factors influencing the continuance intention to the usage of web 2.0: An empirical study. Computers in Human Behavior, 28(3), 933–941.

Cole, M. J., Hendahewa, C., Belkin, N. J., & Shah, C. (2015). User activity patterns during information search. ACM Transactions on Information Systems (TOIS), 33(1), 1–39.

Dupret, G. (2011). Discounted cumulative gain and user decision models. In International symposium on string processing and information retrieval (pp. 2–13). Spire.

Ferguson, C. J. (2016). An effect size primer: A guide for clinicians and researchers. Professional Psychology: Research and Practice, 40(5), 532–538.

Fidel, R. (2012). Human information interaction: An ecological approach to information behavior. Mit Press.

Franque, F. B., Oliveira, T., Tam, C., & de Oliveira Santini, F. (2020). A meta‐analysis of the quantitative studies in continuance intention to use an information system. Internet Research, 31, 123–158.

Gomroki, G., Behzadi, H., Fattahi, R., & Salehi Fadardi, J. (2021). Identifying effective cognitive biases in information retrieval. Journal of Information Science, 49, 348–358.

Hossain, M. A., & Quaddus, M. (2012). Expectation–confirmation theory in information system research: A review and analysis. In Information systems theory (pp. 441–469). Springer.

Huang, Y.‐M. (2019). Examining students' continued use of desktop services: Perspectives from expectation‐confirmation and social influence. Computers in Human Behavior, 96, 23–31.

Kahneman, D. (2003). Maps of bounded rationality: Psychology for behavioral economics. American Economic Review, 93(5), 1449–1475.

Kelly, D., Arguello, J., Edwards, A., & Wu, W.‐C. (2015). Development and evaluation of search tasks for iir experiments using a cognitive complexity framework. In Proceedings of the 2015 international conference on the theory of information retrieval (pp. 101–110). ACM.

Li, Y. (2009). Exploring the relationships between work task and search task in information search. Journal of the American Society for Information Science and Technology, 60(2), 275–291.

Li, Y., & Belkin, N. J. (2008). A faceted approach to conceptualizing tasks in information seeking. Information Processing & Management, 44(6), 1822–1837.

Lipani, A., Carterette, B., & Yilmaz, E. (2019). From a user model for query sessions to session rank biased precision (SRBP). In Proceedings of the 2019 ACM SIGIR international conference on theory of information retrieval (pp. 109–116). ACM.

Liu, C., Liu, Y.‐H., Liu, J., & Bierig, R. (2021). Search interface design and evaluation. Foundations and Trends® in Information Retrieval, 15(3–4), 243–416.

Liu, J. (2023). A behavioral economics approach to interactive information retrieval: Understanding and supporting boundedly rational users (Vol. 48). Springer Nature.

Liu, J., Cole, M. J., Liu, C., Bierig, R., Gwizdka, J., Belkin, N. J., Zhang, J., & Zhang, X. (2010). Search behaviors in different task types. In Proceedings of the 10th annual joint conference on digital libraries (pp. 69–78). ACM.

Liu, J., & Han, F. (2020). Investigating reference dependence effects on user search interaction and satisfaction: A behavioral economics perspective. In Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval (pp. 1141–1150). ACM.

Liu, J., Mitsui, M., Belkin, N. J., & Shah, C. (2019). Task, information seeking intentions, and user behavior: Toward a multilevel understanding of Web search. In Proceedings of the 2019 conference on human information interaction and retrieval (pp. 123–132). ACM.

Liu, J., Sarkar, S., & Shah, C. (2020). Identifying and predicting the states of complex search tasks. In Proceedings of the 2020 conference on human information interaction and retrieval (pp. 193–202). ACM.

Liu, J., & Shah, C. (2019). Investigating the impacts of expectation disconfirmation on web search. In Proceedings of the 2019 conference on human information interaction and retrieval (pp. 319–323). ACM.

Liu, Y.‐H., Thomas, P., Gedeon, T., & Rusnachenko, N. (2022). Search interfaces for biomedical searching: How do gaze, user perception, search behaviour and search performance relate? In Proceedings of the 2022 conference on human information interaction and retrieval (pp. 78–89). ACM.

Luo, C., Liu, Y., Sakai, T., Zhou, K., Zhang, F., Li, X., & Ma, S. (2017). Does document relevance affect the searcher's perception of time? In Proceedings of the tenth ACM international conference on web search and data mining (pp. 141–150). ACM.

Mao, J., Liu, Y., Zhou, K., Nie, J.‐Y., Song, J., Zhang, M., … Luo, H. (2016). When does relevance mean usefulness and user satisfaction in web search? In Proceedings of the 39th international ACM SIGIR conference on research and development in information retrieval (pp. 463–472). ACM.

Marchionini, G. (1995). Information seeking in electronic environments. Cambridge University Press.

Maruping, L. M., Bala, H., Venkatesh, V., & Brown, S. A. (2017). Going beyond intention: Integrating behavioral expectation into the unified theory of acceptance and use of technology. Journal of the Association for Information Science and Technology, 68(3), 623–637.

Maxwell, D., Azzopardi, L., Järvelin, K., & Keskustalo, H. (2015). Searching and stopping: An analysis of stopping rules and strategies. In Proceedings of the 24th ACM CIKM (pp. 313–322). ACM.

McDuff, D., Thomas, P., Craswell, N., Rowan, K., & Czerwinski, M. (2021). Do affective cues validate behavioural metrics for search? In Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval (pp. 1544–1553). ACM.

McGregor, M., Azzopardi, L., & Halvey, M. (2021). Untangling cost, effort, and load in information seeking and retrieval. In Proceedings of the 2021 conference on human information interaction and retrieval (pp. 151–161). ACM.

Moffat, A., Bailey, P., Scholer, F., & Thomas, P. (2017). Incorporating user expectations and behavior into the measurement of search effectiveness. ACM Transactions on Information Systems (TOIS), 35(3), 1–38.

Moffat, A., Mackenzie, J., Thomas, P., & Azzopardi, L. (2022). A flexible framework for offline effectiveness metrics. In Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval (pp. 578–587). ACM.

Moffat, A., Thomas, P., & Scholer, F. (2013). Users versus models: What observation tells us about effectiveness metrics. In Proceedings of the 22nd ACM international conference on information & knowledge management (pp. 659–668). ACM.

Moffat, A., & Zobel, J. (2008). Rank‐biased precision for measurement of retrieval effectiveness. ACM Transactions on Information Systems (TOIS), 27(1), 1–27.

Najaftorkaman, M., Ghapanchi, A. H., Talaei‐Khoei, A., & Ray, P. (2015). A taxonomy of antecedents to user adoption of health information systems: A synthesis of thirty years of research. Journal of the Association for Information Science and Technology, 66(3), 576–598.

Pirolli, P., & Card, S. (1999). Information foraging. Psychological Review, 106(4), 643–675.

Piwowarski, B., Dupret, G., & Lalmas, M. (2012). Beyond cumulated gain and average precision: Including willingness and expectation in the user model (Unpublished doctoral dissertation). Sorbonne Universités, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606.

Pogacar, F. A., Ghenai, A., Smucker, M. D., & Clarke, C. L. (2017). The positive and negative influence of search results on people's decisions about the efficacy of medical treatments. In Proceedings of the ACM SIGIR international conference on theory of information retrieval (pp. 209–216). ACM.

Qazi, A., Tamjidyamcholo, A., Raj, R. G., Hardaker, G., & Standing, C. (2017). Assessing consumers' satisfaction and expectations through online opinions: Expectation and disconfirmation approach. Computers in Human Behavior, 75, 450–460.

Scholer, F., Kelly, D., Wu, W.‐C., Lee, H. S., & Webber, W. (2013). The effect of threshold priming and need for cognition on relevance calibration and assessment. In Proceedings of the 36th international ACM SIGIR conference on research and development in information retrieval (pp. 623–632). ACM.

Shokouhi, M., White, R., & Yilmaz, E. (2015). Anchoring and adjustment in relevance estimation. In Proceedings of the 38th international ACM SIGIR conference on research and development in information retrieval (pp. 963–966). ACM.

Simon, H. A. (2000). Bounded rationality in social science: Today and tomorrow. Mind & Society, 1(1), 25–39.

Steelman, Z. R., & Soror, A. A. (2017). Why do you keep doing that? The biasing effects of mental states on it continued usage intentions. Computers in Human Behavior, 73, 209–223.

Thissen, D., Steinberg, L., & Kuang, D. (2002). Quick and easy implementation of the Benjamini–Hochberg procedure for controlling the false positive rate in multiple comparisons. Journal of Educational and Behavioral Statistics, 27(1), 77–83.

Thomas, P., Kazai, G., White, R., & Craswell, N. (2022). The crowd is made of people: Observations from large‐scale crowd labelling. In ACM SIGIR conference on human information interaction and retrieval (pp. 25–35). ACM.

Thomas, P., Moffat, A., Bailey, P., & Scholer, F. (2014). Modeling decision points in user search behavior. In Proceedings of the 5th information interaction in context symposium (pp. 239–242). ACM.

Tversky, A., & Kahneman, D. (1991). Loss aversion in riskless choice: A reference‐dependent model. The Quarterly Journal of Economics, 106(4), 1039–1061.

Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297–323.

Verma, M., & Yilmaz, E. (2017). Search costs vs. user satisfaction on mobile. In European conference on information retrieval (pp. 698–704). University of Glasgow.

Wang, B., & Liu, J. (2022). Investigating the relationship between in‐situ user expectations and web search behavior. Proceedings of the Association for Information Science and Technology, 59(1), 827–829.

Wang, B., & Liu, J. (2023). Investigating the role of in‐situ user expectations in web search. Information Processing & Management, 60(3), 103300.

Wittek, P., Liu, Y.‐H., Darányi, S., Gedeon, T., & Lim, I. S. (2016). Risk and ambiguity in information seeking: Eye gaze patterns reveal contextual behavior in dealing with uncertainty. Frontiers in Psychology, 7, 1790.

Wu, M., Turpin, A., Thom, J. A., Scholer, F., & Wilkinson, R. (2014). Cost and benefit estimation of experts' mediation in an enterprise search. Journal of the Association for Information Science and Technology, 65(1), 146–163.

Zhang, F., Liu, Y., Li, X., Zhang, M., Xu, Y., & Ma, S. (2017). Evaluating web search with a bejeweled player model. In Proceedings of the 40th international ACM SIGIR conference on research and development in information retrieval (pp. 425–434). ACM.

Zhang, F., Liu, Y., Mao, J., Zhang, M., & Ma, S. (2020). User behavior modeling for web search evaluation. AI Open, 1, 40–56.

Zhang, F., Mao, J., Liu, Y., Xie, X., Ma, W., Zhang, M., & Ma, S. (2020). Models versus satisfaction: Towards a better understanding of evaluation metrics. In Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval (pp. 379–388). ACM.

Zhang, Y. (2014). Beyond quality and accessibility: Source selection in consumer health information searching. Journal of the Association for Information Science and Technology, 65(5), 911–927.