Shi, L., Jayawardena, G., & Gwizdka, J. (2025). Pupillometric Analysis of Cognitive Load in Relation to Relevance and Confirmation Bias. To Appear in Proceedings of the 2025 Conference on Human Information Interaction and Retrieval. CHIIR, New York, NY, USA. Cite

Shi, L., Liu, H., Wong, Y., Mujumdar, U., Zhang, D., Gwizdka, J., & Lease, M. (2024). Argumentative Experience: Reducing Confirmation Bias on Controversial Issues through LLM-Generated Multi-Persona Debates (No. arXiv:2412.04629). arXiv. https://doi.org/10.48550/arXiv.2412.04629 Cite

Mishra, A., Shukla, S., Torres, J., Gwizdka, J., & Roychowdhury, S. (2024). Thought2Text: Text Generation from EEG Signal using Large Language Models (LLMs) (No. arXiv:2410.07507). arXiv. https://doi.org/10.48550/arXiv.2410.07507 Cite

Aliannejadi, M., Gwizdka, J., & Zamani, H. (2024). Interactions with Generative Information Retrieval Systems (No. arXiv:2407.11605). arXiv. http://arxiv.org/abs/2407.11605 Cite

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

Gwizdka, J., & Rieh, S. Y. (2023). Report on the 8th ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2023). SIGIR Forum, 57(1), 9:1-9:7. https://doi.org/10.1145/3636341.3636353 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

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. B. Randolph, & T. Fischer (Eds.), Information Systems and Neuroscience (Vol. 43, pp. 100–110). Springer International Publishing. https://doi.org/10.1007/978-3-030-60073-0_12 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

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

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

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