The DOI matches its Crossref record; 22 of the 29 references it cites were found in a registry or an index.
What are you looking for?: an eye-tracking study of information usage in web search
Abstract
Web search services are among the most heavily used applications on the World Wide Web. Perhaps because search is used in such a huge variety of tasks and contexts, the user interface must strike a careful balance to meet all user needs. We describe a study that used eye tracking methodologies to explore the effects of changes in the presentation of search results. We found that adding information to the contextual snippet significantly improved performance for informational tasks but degraded performance for navigational tasks. We discuss possible reasons for this difference and the design implications for better presentation of search results.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
Broder, A. (2002) · ACM SIGIR Forum · doi:10.1145/792550.792552 · Cited by 1,944
Accurately interpreting clickthrough data as implicit feedback
Joachims, T., Granka, L., Pan, B., Hembrooke, H., & Gay, G. (2005) · Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval · doi:10.1145/1076034.1076063 · Cited by 1,408
Faceted metadata for image search and browsing
Yee, K.-P., Swearingen, K., Li, K., & Hearst, M. A. (2003) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/642611.642681 · Cited by 910
Understanding user goals in web search
Rose, D. E., & Levinson, D. (2004) · Proceedings of the 13th international conference on World Wide Web · doi:10.1145/988672.988675 · Cited by 563
The perfect search engine is not enough
Teevan, J. B., Alvarado, C., Ackerman, M. S., & Karger, D. R. (2004) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/985692.985745 · Cited by 563
Using information scent to model user information needs and actions and the Web
Ed, H., Pirolli, P. L. T., Chen, K., & Pitkow, J. E. (2001) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/365024.365325 · Cited by 418
Automatic identification of user goals in Web search
Lee, U., Liu, Z., & Cho, J. J. (2005) · International World Wide Web Conference (WWW) · doi:10.1145/1060745.1060804 · Cited by 399
Patterns of Search: Analyzing and Modeling Web Query Refinement
Lau, T. A., & Horvitz, E. (1999) · Courses and lectures · doi:10.1007/978-3-7091-2490-1_12 · Cited by 254
The influence of task and gender on search and evaluation behavior using Google
Lorigo, L., Pan, B., Hembrooke, H. A., Joachims, T., Granka, L. A., & Gay, G. K. (2005) · Information Processing & Management · doi:10.1016/j.ipm.2005.10.001 · Cited by 252
An eye tracking study of the effect of target rank on web search
Guan, Z., & Cutrell, E. B. (2007) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240691 · Cited by 243
Self-citation
Research works printed but not linked: 4
- 10.5555/317328.317340 · DOI
- 10.1002/asi.v56:9 · DOI
- Rele , R.S. and Duchowski , A.T . Using eye tracking to evaluate alternate search results interfaces . In Proc. HFES,49th Annual Meeting ( 2005 ). Rele, R.S. and Duchowski, A.T. Using eye tracking to evaluate alternate search results interfaces. In Proc. HFES,49th Annual Meeting (2005).
- 10.1002/asi.v57:6 · DOI
Cited by
Sorted by citations
Measuring personalization of web search
Hannak, A., Sapiezynski, P., Molavi Kakhki, A., Krishnamurthy, B., Lazer, D., Mislove, A., & Wilson, C. (2013) · Proceedings of the 22nd international conference on World Wide Web · doi:10.1145/2488388.2488435 · Cited by 396
Huang, J. J. S., White, R. W., & Dumais, S. (2011) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979125 · Cited by 270
Understanding PubMed(R) user search behavior through log analysis
Islamaj Dogan, R., Murray, G. C., Neveol, A., & Lu, Z. (2009) · Database · doi:10.1093/database/bap018 · Cited by 265
What do you see when you're surfing?
Buscher, G., Cutrell, E. B., & Morris, M. R. (2009) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1518701.1518705 · Cited by 254
Self-citationCROSSROADS—Identifying Viable “Need–Solution Pairs”: Problem Solving Without Problem Formulation
von Hippel, E., & von Krogh, G. (2015) · Organization Science · doi:10.1287/orsc.2015.1023 · Cited by 256
An eye tracking study of the effect of target rank on web search
Guan, Z., & Cutrell, E. B. (2007) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240691 · Cited by 243
Self-citationHasanzadeh, S., Esmaeili, B., & Dodd, M. D. (2018) · Journal of Construction Engineering and Management · doi:10.1061/(asce)co.1943-7862.0001516 · Cited by 217
Huang, J. J. S., White, R. W., & Buscher, G. (2012) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2207676.2208591 · Cited by 206
Mining query logs: turning search usage data into knowledge
Silvestri, F. (2009) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000013 · Cited by 194
Lalmas, M., O’Brien, H., & Yom-Tov, E. (2015) · Synthesis Lectures on Information Concepts, Retrieval, and Services · doi:10.1007/978-3-031-02289-0 · Cited by 192
Gerjets, P. H., Kammerer, Y., & Werner, B. (2010) · Learning and Instruction · doi:10.1016/j.learninstruc.2010.02.005 · Cited by 186
Augmenting web pages and search results to support credibility assessment
Schwarz, J., & Morris, M. (2011) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979127 · Cited by 181
What do developers search for on the web?
Xia, X., Bao, L., Lo, D., Kochhar, P. S., Hassan, A. E., & Xing, Z. (2017) · Empirical Software Engineering · doi:10.1007/s10664-017-9514-4 · Cited by 174
Good abandonment in mobile and PC internet search
Li, J., Huffman, S. B., & Tokuda, A. (2009) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/1571941.1571951 · Cited by 158
Guo, Q., & Agichtein, E. (2012) · International World Wide Web Conference (WWW) · doi:10.1145/2187836.2187914 · Cited by 154
What do exploratory searchers look at in a faceted search interface?
Kules, B., Capra, R., Banta, M., & Sierra, T. (2009) · ACM/IEEE Joint Conference on Digital Libraries · doi:10.1145/1555400.1555452 · Cited by 154
Athukorala, K., Głowacka, D., Jacucci, G., Oulasvirta, A., & Vreeken, J. (2016) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23617 · Cited by 150
The impact of identifier style on effort and comprehension
Binkley, D., Davis, M. H., Lawrie, D., Maletic, J. I., Morrell, C. H., & Sharif, B. (2012) · Empirical Software Engineering · doi:10.1007/s10664-012-9201-4 · Cited by 147
Ready to buy or just browsing?
Guo, Q., & Agichtein, E. (2010) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/1835449.1835473 · Cited by 145
The good, the bad, and the random
Buscher, G., Dumais, S., & Cutrell, E. B. (2010) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/1835449.1835459 · Cited by 145
Self-citationAn Eye Tracking Study on camelCase and under_score Identifier Styles
Sharif, B., & Maletic, J. I. (2010) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1109/icpc.2010.41 · Cited by 144
Hoffmann, R., Fogarty, J. A., & Weld, D. S. (2007) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/1294211.1294216 · Cited by 131
Online Evaluation for Information Retrieval
Hofmann, K., Li, L. C., & Radlinski, F. (2016) · now publishers, Inc. eBooks · doi:10.1561/1500000051 · Cited by 141
Kammerer, Y., Bråten, I., Gerjets, P., & Strømsø, H. I. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2012.10.012 · Cited by 129
Arif, N., Al-Jefri, M. M., Bizzi, I. H., Perano, G. B., Goldman, M., Haq, I., Chua, K. L., Mengozzi, M., Neunez, M., Smith, H. E., et al. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.01215 · Cited by 128
Conversational Information Seeking
Zamani, H., Trippas, J. R., Dalton, J., & Radlinski, F. (2023) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000081 · Cited by 178
Searching, browsing, and clicking in a search session
Jiang, J., He, D., & Allan, J. (2014) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2600428.2609633 · Cited by 123
From Keyword Search to Exploration: Designing Future Search Interfaces for the Web
Wilson, M. L., Bill, K., schraefel, M. C., & Shneiderman, B. (2010) · Foundations and Trends® in Web Science · doi:10.1561/1800000003 · Cited by 128
Towards predicting web searcher gaze position from mouse movements
Guo, Q., & Agichtein, E. (2010) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/1753846.1754025 · Cited by 121
The influence of caption features on clickthrough patterns in web search
Clarke, C. L. A., Agichtein, E., Dumais, S., & White, R. W. (2007) · Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval · doi:10.1145/1277741.1277767 · Cited by 119
Hotmap: Looking at Geographic Attention
Fisher, D. (2007) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2007.70561 · Cited by 117
SearchGazer: Webcam Eye Tracking for Remote Studies of Web Search
Papoutsaki, A., Laskey, J., & Huang, J. (2017) · Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval · doi:10.1145/3020165.3020170 · Cited by 116
Buscher, G., Dengel, A., Biedert, R., & van Elst, L. (2012) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/2070719.2070722 · Cited by 116
Source evaluation of domain experts and novices during Web search
Brand‐Gruwel, S., Kammerer, Y., van Meeuwen, L. W., & van Gog, T. (2017) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12162 · Cited by 127
Jain, V., & Varma, M. (2011) · International World Wide Web Conference (WWW) · doi:10.1145/1963405.1963447 · Cited by 115
Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts
Navalpakkam, V., Jentzsch, L., Sayres, R., Ravi, S., Ahmed, A. A., & Smola, A. J. (2013) · International World Wide Web Conference (WWW) · doi:10.1145/2488388.2488471 · Cited by 107
Individual differences in gaze patterns for web search
Dumais, S., Buscher, G., & Cutrell, E. B. (2010) · Information Interaction in Context Symposium (IIiX) · doi:10.1145/1840784.1840812 · Cited by 104
Self-citationKammerer, Y., & Gerjets, P. H. (2013) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2013.846790 · Cited by 114
Evaluating the retrieval effectiveness of web search engines using a representative query sample
Lewandowski, D. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23304 · Cited by 98
Direct answers for search queries in the long tail
Bernstein, M. S., Teevan, J., Dumais, S., Liebling, D., & Horvitz, E. (2012) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/2207676.2207710 · Cited by 97
Oulasvirta, A., Hukkinen, J. P., & Schwartz, B. N. (2009) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/1571941.1572030 · Cited by 108
Kim, N. W., Bylinskii, Z., Borkin, M. A., Gajos, K. Z., Oliva, A., Durand, F., & Pfister, H. (2017) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3131275 · Cited by 95
Scanpath clustering and aggregation
Goldberg, J. H., & Helfman, J. I. (2010) · ACM Symposium on Eye Tracking Research and Applications (ETRA) · doi:10.1145/1743666.1743721 · Cited by 92
Query expansion using gaze-based feedback on the subdocument level
Buscher, G., Dengel, A. R., & van Elst, L. (2008) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/1390334.1390401 · Cited by 91
Improving searcher models using mouse cursor activity
Huang, J. J. S., White, R. W., Buscher, G., & Wang, K. (2012) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2348283.2348313 · Cited by 91
An Eye-tracking Study of User Interactions with Query Auto Completion
Hofmann, K., Mitra, B., Radlinski, F., & Shokouhi, M. (2014) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/2661829.2661922 · Cited by 90
Ironies of Generative AI: Understanding and Mitigating Productivity Loss in Human-AI Interaction
Simkute, A., Tankelevitch, L., Kewenig, V., Scott, A. E., Sellen, A., & Rintel, S. (2024) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2024.2405782 · Cited by 89
“Similarly Cutrell et al. (2000), found that users interrupted earlier in a task were more likely to request a reminder after being interrupted, and Cutrell and Guan (2007) showed that the later in the main task an interruption occurs, the less recovery time is needed when subsequently returning to…”
Inferring user knowledge level from eye movement patterns
Cole, M., Jacek Gwizdka, A., Liu, C., Belkin, N. J., & Zhang, X. (2012) · Information Processing & Management · doi:10.1016/j.ipm.2012.08.004 · Cited by 86
Lewandowski, D., & Kammerer, Y. (2020) · Behaviour and Information Technology · doi:10.1080/0144929x.2020.1761450 · Cited by 84
(2024) · ACM eBooks · doi:10.1145/3674127 · Cited by 86
Lalmas, M., O'Brien, H., & Yom‐Tov, E. (2014) · Synthesis lectures on information concepts, retrieval, and services · doi:10.2200/s00605ed1v01y201410icr038 · Cited by 95
Large-scale analysis of individual and task differences in search result page examination strategies
Buscher, G., White, R. W., Dumais, S., & Huang, J. J. S. (2012) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/2124295.2124341 · Cited by 78
Eye‐tracking analysis of user behavior and performance in web search on large and small screens
Kim, J., Thomas, P., Sankaranarayana, R. S., Gedeon, T., & Yoon, H. (2014) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23187 · Cited by 76
Searching the Web for conflicting topics: Page and user factors
Salmerón, L., Kammerer, Y., & García-Carrión, P. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.04.034 · Cited by 76
Shen, C., & Zhao, Q. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10584-0_3 · Cited by 74
Kelly, D., & Azzopardi, L. A. (2015) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2766462.2767732 · Cited by 80
Diriye, A., White, R. W., Buscher, G., & Dumais, S. (2012) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/2396761.2398399 · Cited by 68
Balatsoukas, P., & Ruthven, I. (2012) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22707 · Cited by 66
Large interactive visualization of density functions on big data infrastructure
Perrot, A., Bourqui, R., Hanusse, N., Lalanne, F., & Auber, D. (2015) · IEEE Symposium on Large Data Analysis and Visualization · doi:10.1109/ldav.2015.7348077 · Cited by 63
Agrawal, R., Halverson, A., Kenthapadi, K., Mishra, N., & Tsaparas, P. (2009) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/1498759.1498824 · Cited by 66
Ying, A. T. T., & Robillard, M. P. (2013) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/2491411.2494587 · Cited by 62
Recognition of understanding level and language skill using measurements of reading behavior
Martínez-Gómez, P., & Aizawa, A. (2014) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/2557500.2557546 · Cited by 63
Improving Search Results Quality by Customizing Summary Lengths
Kaißer, M., Hearst, M. A., & Lowe, J. B. (2008) · Cited by 61
A Study of Snippet Length and Informativeness
Maxwell, D., Azzopardi, L. A., & Moshfeghi, Y. (2017) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3077136.3080824 · Cited by 60
Discriminating the relevance of web search results with measures of pupil size
Oliveira, F. T. P., Aula, A., & Russell, D. M. (2009) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1518701.1519038 · Cited by 60
Addressing people's information needs directly in a web search result page
Chilton, L. B., & Teevan, J. B. (2011) · International World Wide Web Conference (WWW) · doi:10.1145/1963405.1963413 · Cited by 58
Influence of Vertical Result in Web Search Examination
Liu, Z., Liu, Y., Zhou, K., Zhang, M., & Ma, S. (2015) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2766462.2767714 · Cited by 55
Attention Allocation in Information-Rich Environments: The Case of News Aggregators
Dellarocas, C. N., Sutanto, J., Calin, M., & Palme, E. (2015) · Management Science · doi:10.1287/mnsc.2015.2237 · Cited by 62
Liu, Y., Wang, C., Zhou, K., Nie, J., Zhang, M., & Ma, S. (2014) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/2661829.2661907 · Cited by 54
Adaptive Visualization of Search Results: Bringing User Models to Visual Analytics
Ahn, J., & Brusilovsky, P. L. (2009) · Information Visualization · doi:10.1057/ivs.2009.12 · Cited by 53
Can relevance of images be inferred from eye movements?
Arto Klami, A., Saunders, C. J., de Campos, T. E., & Samuel Kaski, A. (2008) · Multimedia Information Retrieval · doi:10.1145/1460096.1460120 · Cited by 52
Kong, N., Grossman, T., Hartmann, B., Agrawala, M., & Fitzmaurice, G. W. (2012) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2207676.2208549 · Cited by 52
Taking It All In? Visual Attention in Microblog Consumption
Counts, S., & Fisher, K. J. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v5i1.14103 · Cited by 52
Everything you always wanted to know about a dataset: Studies in data summarisation
Koesten, L., Simperl, E., Blount, T., Kacprzak, E., & Tennison, J. (2020) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2019.10.004 · Cited by 51
Discovering common motifs in cursor movement data for improving web search
Lagun, D., Сергеевич, А. М., Guo, Q., & Agichtein, E. (2014) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/2556195.2556265 · Cited by 51
Using eye movement data to infer human behavioral intentions
Hyeonggyu, P., Lee, S., Lee, M., Chang, M.-S., & Kwak, H.-W. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.06.016 · Cited by 51
Auditing the Partisanship of Google Search Snippets
Hu, D., Jiang, S., Robertson, R. E., & Wilson, C. (2019) · International World Wide Web Conference (WWW) · doi:10.1145/3308558.3313654 · Cited by 51
Enhanced results for web search
Haas, K., Mika, P., Tarjan, P., & Blanco, R. (2011) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2009916.2010014 · Cited by 50
Edmonds, A., White, R. W., Morris, D., & Drucker, S. M. (2007) · Journal of Web Engineering · Cited by 49
Incorporating Non-sequential Behavior into Click Models
Wang, C., Liu, Y., Wang, M., Zhou, K., Nie, J., & Ma, S. (2015) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2766462.2767712 · Cited by 50
Lagun, D., & Agichtein, E. (2011) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2009916.2009967 · Cited by 49
Kammerer, Y., & Gerjets, P. H. (2012) · Library and information science · doi:10.1108/s1876-0562(2012)002012a012 · Cited by 48
Using information scent and need for cognition to understand online search behavior
Wu, W., Kelly, D., & Sud, A. (2014) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2600428.2609626 · Cited by 52
The presentation of health-related search results and its impact on negative emotional outcomes
Lauckner, C., & Hsieh, G. (2013) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2470654.2470702 · Cited by 48
Effects of task complexity on online search behavior of adolescents
Walhout, J., Oomen, P., Jarodzka, H. M., & Brand‐Gruwel, S. (2017) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23782 · Cited by 48
Using Information Scent to Understand Mobile and Desktop Web Search Behavior
Ong, K., Järvelin, K., Sanderson, M., & Scholer, F. (2017) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3077136.3080817 · Cited by 47
Battery-Free Eye Tracker on Glasses
Li, T., & Zhou, X. (2018) · ACM Annual International Conference on Mobile Computing and Networking (MobiCom) · doi:10.1145/3241539.3241578 · Cited by 47
Health information quality of websites on periodontology
Bizzi, I. H., Ghezzi, P., & Paudyal, P. (2016) · Journal Of Clinical Periodontology · doi:10.1111/jcpe.12668 · Cited by 46
Ten Social Dimensions of Conversations and Relationships
Choi, M., Aiello, L. M., Varga, K. Z., & Quercia, D. (2020) · International World Wide Web Conference (WWW) · doi:10.1145/3366423.3380224 · Cited by 49
Inferring search behaviors using partially observable Markov (POM) model
Wang, K., Gloy, N., & Li, X. (2010) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/1718487.1718514 · Cited by 45
The deliberative influence of comment section structure
Peacock, C., Scacco, J. M., & Stroud, N. J. (2017) · Journalism · doi:10.1177/1464884917711791 · Cited by 45
Kammerer, Y., & Gerjets, P. H. (2010) · ACM Symposium on Eye Tracking Research and Applications (ETRA) · doi:10.1145/1743666.1743736 · Cited by 44
Understanding Reading Attention Distribution during Relevance Judgement
Li, X., Liu, Y., Mao, J., He, Z., Zhang, M., & Ma, S. (2018) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3269206.3271764 · Cited by 43
Kules, B., & Capra, R. (2011) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21647 · Cited by 45
An Eye-Tracking Study of Query Reformulation
Eickhoff, C., Dungs, S., & Tran, V. (2015) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2766462.2767703 · Cited by 42
Wittek, P., Liu, Y., Darányi, S., Gedeon, T., & Lim, I. S. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.01790 · Cited by 44
The evaluation of a mobile user interface for people on the autism spectrum: An eye movement study
Rezae, M., Chen, N. T. M., McMeekin, D. A., Tan, T., Krishna, A., & Lee, H. (2020) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2020.102462 · Cited by 47
Social annotations in web search
Muralidharan, A. S., Gyöngyi, Z., & Ed, H. (2012) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2207676.2208554 · Cited by 43
A Survey on Visual Information Search Behavior and Requirements of Radiologists
Holzer, M., Dungs, S., Vargas, A., Langs, G., Kriewel, S., Müller, H., & Markonis, D. (2012) · Methods of Information in Medicine · doi:10.3414/me11-02-0025 · Cited by 40
Fast and reliable online learning to rank for information retrieval
Hofmann, K. (2013) · ACM SIGIR Forum · doi:10.1145/2568388.2568413 · Cited by 40
Metadata
- Authors
- Cutrell, E., & Guan, Z.
- Affiliations
- Microsoft (United States) (US)
- University of Washington (US)
- ORCID
- Cutrell, Edward
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2007-04-29
- Pages
- 407-416
- OpenAlex
- W2004089651
- Cited by
- 460
- References
- 29
- Citations by year
- 2026: 7 · 2025: 6 · 2024: 30 · 2023: 13 · 2022: 10 · 2021: 12 · 2020: 24 · 2019: 15 · 2018: 24 · 2017: 41 · 2016: 28 · 2015: 34 · 2014: 39 · 2013: 34 · 2012: 38
- FWCI
- 19.36
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Keywords
- web search, search result presentation, eye tracking, user interface design
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review