Jones, W., Capra, R., Czerwinski, M., Dinneen, J. D., Gwizdka, J., & Karadkar, U. (2024). PIM 2024: The Information We Need, When We Need It…: As We Get Ever Closer, Is this Ideal Still Ideal? Proceedings of the 2024 Conference on Human Information Interaction and Retrieval, 438–440. https://doi.org/10.1145/3627508.3638333 Cite

Shi, L., & Gwizdka, J. (2024). The Effects of Confirmation Bias and Readability on Relevance Assessment: an Eye-tracking Study. In R. Riedl, J. vom Brocke, P.-M. Léger, A. B. Randolph, G. Müller-Putz, & F. D. Davis (Eds.), Information Systems and Neuroscience. Springer International Publishing. Cite

Bautista, J. R., Zhang, Y., Gwizdka, J., & Chang, Y.-S. (2023). Consumers’ longitudinal health information needs and seeking: a scoping review. Health Promotion International, 38(4), daad066. https://doi.org/10.1093/heapro/daad066 Cite

Gwizdka, J., & Rieh, S. Y. (2023). Report on the 8th ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2023). SIGIR Forum, 57. Cite

Bautista, J. R., Zhang, Y., & Gwizdka, J. (2023). Correcting vaccine misinformation on social media: Effect of social correction methods on vaccine skeptics’ intention to take COVID-19 vaccine. New Media & Society, 14614448231169696. https://doi.org/10.1177/14614448231169697 Cite

Shi, L., Bhattacharya, N., Das, A., & Gwizdka, J. (2023). True or false? Cognitive load when reading COVID-19 news headlines: an eye-tracking study. Proceedings of the 2023 Conference on Human Information Interaction and Retrieval, 107–116. https://doi.org/10.1145/3576840.3578290 Cite

Shi, L., Rahman, R., Melamed, E., Gwizdka, J., Rousseau, J. F., & Ding, Y. (2023). Using Explainable AI to Cross-Validate Socio-economic Disparities Among Covid-19 Patient Mortality (No. arXiv:2302.08605). arXiv. http://arxiv.org/abs/2302.08605 Cite

Gwizdka, J. (2023). NeuroIS at 15: What Were We Writing About? In F. D. Davis, R. Riedl, J. vom Brocke, P.-M. Léger, A. B. Randolph, & G. Müller-Putz (Eds.), Information Systems and Neuroscience. Springer International Publishing. Cite

Gwizdka, J., & Rieh, S. Y. (Eds.). (2023). CHIIR ’23: Proceedings of the 2023 conference on human information interaction and retrieval. Association for Computing Machinery. Cite

Seaborn, K., Henderson, K., Gwizdka, J., & Chignell, M. (2022). A meta-review of psychological resilience during COVID-19. Npj Mental Health Research, 1(1), 1–9. https://doi.org/10.1038/s44184-022-00005-8 Cite

Bautista, J. R., Zhang, Y., & Gwizdka, J. (2022). Professional Identity and Perceived Crisis Severity as Antecedents of Healthcare Professionals’ Responses to Health Misinformation on Social Media. In M. Smits (Ed.), iConference 2022 (pp. 273–291). Springer International Publishing. https://doi.org/10.1007/978-3-030-96960-8_19 Cite

Bautista, J. R., Zhang, Y., & Gwizdka, J. (2022). Predicting healthcare professionals’ intention to correct health misinformation on social media. Telematics & Informatics. Cite

Gwizdka, J., Tessmer, R., Chan, Y.-C., Radhakrishnan, K., & Henry, M. (2022). Eye-gaze and mouse-movements on web search as indicators of cognitive impairment. In F. D. Davis, R. Riedl, J. vom Brocke, P.-M. Léger, A. B. Randolph, & G. Müller-Putz (Eds.), Information Systems and Neuroscience. Springer International Publishing. Cite

Shi, L., Bhattacharya, N., Das, A., Lease, M., & Gwizdka, J. (2022). The Effects of Interactive AI Design on User Behavior: An Eye-tracking Study of Fact-checking COVID-19 Claims. ACM SIGIR Conference on Human Information Interaction and Retrieval, 315–320. https://doi.org/10.1145/3498366.3505786 Cite

Chang, Y.-S., & Gwizdka, J. (2022). Perceived eHealth Literacy vis-a-vis Information Search Outcome: A Quasi-Experimental Study. ACM SIGIR Conference on Human Information Interaction and Retrieval, 305–309. https://doi.org/10.1145/3498366.3505825 Cite

Bautista, J. R., Zhang, Y., & Gwizdka, J. (2022). Professional identity and perceived crisis severity as antecedents of healthcare professionals’ responses to health misinformation on social media. To Appear in IConference 2022, 104375. https://doi.org/10.1016/j.ijmedinf.2021.104375 Cite

Rubin, M., Bhattacharya, N., Gwizdka, J., Griffin, Z., & Telch, M. (2021). The influence of PTSD symptoms on selective visual attention while reading. Cognition and Emotion, 36(3), 527–534. https://doi.org/10.1080/02699931.2021.2016639 Cite

Bhattacharya, N., & Gwizdka, J. (2021). YASBIL: Yet Another Search Behaviour (and) Interaction Logger. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2585–2589. https://doi.org/10.1145/3404835.3462800 Cite

Seaborn, K., Chignell, M., & Gwizdka, J. (2021). Psychological resilience during COVID-19: a meta-review protocol. BMJ Open, 11(6), e051417. https://doi.org/10.1136/bmjopen-2021-051417 Cite

Chang, Y.-S., Zhang, Y., & Gwizdka, J. (2021). The effects of information source and eHealth literacy on consumer health information credibility evaluation behavior. Computers in Human Behavior, 115, 106629. https://doi.org/10.1016/j.chb.2020.106629 Cite

Bautista, J. R., Zhang, Y., & Gwizdka, J. (2021). Healthcare professionals’ acts of correcting health misinformation on social media. International Journal of Medical Informatics, 104375. https://doi.org/10.1016/j.ijmedinf.2021.104375 Cite

Bhattacharya, N., & Gwizdka, J. (2021). A Triangulation Perspective for Search as Learning. Proceedings of the Second International Workshop on Investigating Learning During (Web) Search (IWILDS) Co-Located with 30th ACM International Conference on Information and Knowledge Management (CIKM 2021). IWILDS’2021. Cite

Chang, Y.-S., Zhang, Y., & Gwizdka, J. (2021). Predicting Surrogates’ Health Information Seeking Behavior via Information Source and Information Evaluation. Proceedings of the Association for Information Science and Technology. ASIST’2021. Cite

Gwizdka, J. (2021). “Overloading” Cognitive (Work)Load:  What Are We Really Measuring? Information Systems and Neuroscience. NeuroIS Retreat 2021. Cite

Wu, D., Dong, J., Shi, L., Liu, C., & Ding, J. (2020). Credibility assessment of good abandonment results in mobile search. Information Processing & Management, 57(6), 102350. https://doi.org/10.1016/j.ipm.2020.102350 Cite

Bhattacharya, N., & Gwizdka, J. (2020). Visualizing and Quantifying Vocabulary Learning During Search. Proceedings of the First International Workshop on Investigating Learning During (Web) Search (IWILDS) Co-Located with 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2699, 4. http://ceur-ws.org/Vol-2699/paper22.pdf Cite

Bhattacharya, N., Rakshit, S., & Gwizdka, J. (2020). Towards Real-time Webpage Relevance Prediction UsingConvex Hull Based Eye-tracking Features. ACM Symposium on Eye Tracking Research and Applications, 1–10. https://doi.org/10.1145/3379157.3391302 Cite

Bhattacharya, N., Rakshit, S., Gwizdka, J., & Kogut, P. (2020). Relevance Prediction from Eye-movements Using Semi-interpretable Convolutional Neural Networks. Proceedings of the 2020 Conference on Human Information Interaction and Retrieval, 223–233. https://doi.org/10.1145/3343413.3377960 Cite

Tsai, T.-H., Lin, W.-Y., Chang, Y.-S., Chang, P.-C., & Lee, M.-Y. (2020). Technology anxiety and resistance to change behavioral study of a wearable cardiac warming system using an extended TAM for older adults. PLOS ONE, 15(1), e0227270. https://doi.org/10.1371/journal.pone.0227270 Cite

Jia, C., & Gwizdka, J. (2020). An eye-tracking study of differences in reading between automated and human-written news. In F. D. Davis, R. Riedl, J. vom Brocke, P.-M. Léger, A. Randolph, & T. Fischer (Eds.), NeuroIS’2020. Cite

Gwizdka, J., & Chang, Y.-S. (2020). Search Results Viewing Behavior vis-à-vis Relevance Criteria. In F. D. Davis, R. Riedl, J. vom Brocke, P.-M. Léger, A. Randolph, & T. Fischer (Eds.), Information Systems and Neuroscience (pp. 181–188). Springer International Publishing. https://doi.org/10.1007/978-3-030-28144-1_20 Cite

Gwizdka, J., & Dillon, A. (2020). Eye-Tracking as a Method for Enhancing Research on Information Search. In W. T. Fu & H. van Oostendorp (Eds.), Understanding and Improving Information Search: A Cognitive Approach (pp. 161–181). Springer International Publishing. https://doi.org/10.1007/978-3-030-38825-6_9 Cite

Bhattacharya, N., Li, Q., & Gurari, D. (2019, October). Why Does a Visual Question Have Different Answers? The IEEE International Conference on Computer Vision (ICCV). Cite

Soboczenski, F., Trikalinos, T. A., Kuiper, J., Bias, R. G., Wallace, B. C., & Marshall, I. J. (2019). Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study. BMC Medical Informatics & Decision Making, 19(1), N.PAG-N.PAG. rzh. https://doi.org/10.1186/s12911-019-0814-z Cite

Sun, Y., Zhang, Y., Gwizdka, J., & Trace, C. B. (2019). Consumer Evaluation of the Quality of Online Health Information: Systematic Literature Review of Relevant Criteria and Indicators. Journal of Medical Internet Research, 21(5), e12522. https://doi.org/10.2196/12522 Cite

Gwizdka, J., Zhang, Y., & Dillon, A. (2019). Using the eye-tracking method to study consumer online health information search behaviour. Aslib Journal of Information Management, 71(6), 739–754. https://doi.org/10.1108/AJIM-02-2019-0050 Cite

Gwizdka, J. (2019). Exploring Eye-Tracking Data for Detection of Mind-Wandering on Web Tasks. In F. D. Davis, R. Riedl, J. vom Brocke, P.-M. Léger, & A. B. Randolph (Eds.), Information Systems and Neuroscience (pp. 47–55). Springer International Publishing. https://doi.org/10.1007/978-3-030-01087-4_6 Cite

Gwizdka, J., Moshfeghi, Y., & Wilson, M. L. (2019). Introduction to the special issue on neuro-information science. Journal of the Association for Information Science and Technology, 70(9), 911–916. https://doi.org/10.1002/asi.24263 Cite

Ebeid, I. A., Bhattacharya, N., Gwizdka, J., & Sarkar, A. (2019). Analyzing Gaze Transition Behavior Using Bayesian Mixed Effects Markov Models. Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications, 5:1-5:5. https://doi.org/10.1145/3314111.3319839 Cite

Bhattacharya, N., & Gwizdka, J. (2019). Measuring Learning During Search: Differences in Interactions, Eye-Gaze, and Semantic Similarity to Expert Knowledge. Proceedings of the 2019 Conference on Human Information Interaction and Retrieval, 63–71. https://doi.org/10.1145/3295750.3298926 Cite

Bilal, D., & Gwizdka, J. (2018). Children’s query types and reformulations in Google search. Information Processing & Management, 54(6), 1022–1041. https://doi.org/10.1016/j.ipm.2018.06.008 Cite

Gwizdka, J. (2018). Inferring Web Page Relevance Using Pupillometry and Single Channel EEG. In F. D. Davis, R. Riedl, J. vom Brocke, P.-M. Léger, & A. B. Randolph (Eds.), Information Systems and Neuroscience (74; pp. 175–183). Springer International Publishing. https://doi.org/10.1007/978-3-319-67431-5_20 Cite

Bhattacharya, N., & Gwizdka, J. (2018). Relating Eye-tracking Measures with Changes in Knowledge on Search Tasks. Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications, 62:1-62:5. https://doi.org/10.1145/3204493.3204579 Cite

Chang, Y.-S., & Gwizdka, J. (2018). Relevance criteria dynamics: A study of online news selection on SERPs. Proceedings of the Association for Information Science and Technology, 55(1), 768–769. https://doi.org/10.1002/pra2.2018.14505501108 Cite

Gwizdka, J. (2018). Neuro-physiological data as a source of evaluation metrics for personalized IR. Proceedings of the Workshop on Evaluation of Personalisation in Information Retrieval - WEPIR’2018 Held at ACM SIGIR CHIIR’2018. Workshop on Evaluation of Personalisation in Information Retrieval - WEPIR’2018, New Brunswick, NJ, USA. Cite

Ebeid, I. A., & Gwizdka, J. (2018). Real-time Gaze Transition Entropy. Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications, 94:1-94:3. https://doi.org/10.1145/3204493.3208340 Cite

Gwizdka, J., Hosseini, R., Cole, M., & Wang, S. (2017). Temporal dynamics of eye-tracking and EEG during reading and relevance decisions. Journal of the Association for Information Science and Technology, 68(10), 2299–2312. https://doi.org/10.1002/asi.23904 Cite

Eickhoff, C., Gwizdka, J., Hauff, C., & He, J. (2017). Introduction to the special issue on search as learning. Information Retrieval Journal, 20(5), 399–402. https://doi.org/10.1007/s10791-017-9315-9 Cite

Smith, C. L., Gwizdka, J., & Feild, H. (2017). The use of query auto-completion over the course of search sessions with multifaceted information needs. Information Processing & Management, 53(5), 1139–1155. https://doi.org/10.1016/j.ipm.2017.05.001 Cite

Tsai, T.-H., Chang, H.-T., Chen, Y.-J., & Chang, Y.-S. (2017). Determinants of user acceptance of a specific social platform for older adults: An empirical examination of user interface characteristics and behavioral intention. PLOS ONE, 12(8), e0180102. https://doi.org/10.1371/journal.pone.0180102 Cite