Publications - Jacek Gwizdka

My publications can also be found at: GoogleScholar | Academia.edu | ResearchGate | Orchid ID | Researcher ID

G-Scholar citations: 5821 h-index: 42 (h-index since 2020: 26) i10-index: 93

Note: list of publications is generated automatically with Zotpress. Thanks to Dr. Katie Seaborn for this useful plug-in!

Categorization of publications may be slightly incorrect. Journal Article contain both refereed (most) and non-refereed articles. Conference Paper section includes long, short, and workshop papers.

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Shi, L., Jayawardena, G., & Gwizdka, J. (2025). Pupillometric Analysis of Cognitive Load in Relation to Relevance and Confirmation Bias. Proceedings of the 2025 ACM SIGIR Conference on Human Information Interaction and Retrieval, 219–230. https://doi.org/10.1145/3698204.3716458 Cite

Gwizdka, J., & Cole, M. (2025). g-Rel-READER: A Dataset for Relevance and Reading Evaluation through Advanced Data from Eye-tracking and EEG Recordings. Proceedings of the 2025 ACM SIGIR Conference on Human Information Interaction and Retrieval, 377–381. https://doi.org/10.1145/3698204.3716474 Cite

Mishra, A., Shukla, S., Torres, J., Gwizdka, J., & Roychowdhury, S. (2025). Thought2Text: Text Generation from EEG Signal using Large Language Models (LLMs). In L. Chiruzzo, A. Ritter, & L. Wang (Eds.), Findings of the Association for Computational Linguistics: NAACL 2025 (pp. 3747–3759). Association for Computational Linguistics. https://aclanthology.org/2025.findings-naacl.207/ Cite

Shukla, S., Torres, J., Mishra, A., Gwizdka, J., & Roychowdhury, S. (2025, February 17). A Survey on Bridging EEG Signals and Generative AI: From Image and Text to Beyond. ArXiv.Org. https://arxiv.org/abs/2502.12048v1 Cite

Aliannejadi, M., Gwizdka, J., & Zamani, H. (2025). Interactions with Generative Information Retrieval Systems. In R. W. White & C. Shah (Eds.), Information Access in the Era of Generative AI (pp. 47–71). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-73147-1_3 Cite

Liu, H., Gwizdka, J., & Lease, M. (2024). Exploring Multidimensional Checkworthiness: Designing AI-assisted Claim Prioritization for Human Fact-checkers (No. arXiv:2412.08185). arXiv. https://doi.org/10.48550/arXiv.2412.08185 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

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

Gwizdka, J. (2024). g-Rel-READER. OSF. https://doi.org/10.17605/OSF.IO/3BVTX 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

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

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

Bautista, J. R., Zhang, Y., & Gwizdka, J. (2022). Predicting healthcare professionals’ intention to correct health misinformation on social media. Telematics and Informatics, 73, 101864. https://doi.org/10.1016/j.tele.2022.101864 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

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

Gwizdka, J., Tessmer, R., Chan, Y.-C., Radhakrishnan, K., & Henry, M. L. (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. R. Müller-Putz (Eds.), Information Systems and Neuroscience (pp. 187–200). Springer International Publishing. https://doi.org/10.1007/978-3-031-13064-9_20 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

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

Bautista, J. R., Zhang, Y., & Gwizdka, J. (2021). US Physicians’ and Nurses’ Motivations, Barriers, and Recommendations for Correcting Health Misinformation on Social Media: Qualitative Interview Study. JMIR Public Health and Surveillance, 7(9), e27715. https://doi.org/10.2196/27715 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

Bautista, J. R., Zhang, Y., & Gwizdka, J. (2021). Healthcare professionals’ acts of correcting health misinformation on social media. International Journal of Medical Informatics, 148, 104375. https://doi.org/10.1016/j.ijmedinf.2021.104375 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

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, 58, 36–47. https://doi.org/10.1002/pra2.434 Cite

Gwizdka, J. (2021). “Overloading” Cognitive (Work)Load: What Are We Really Measuring? In F. D. Davis, R. Riedl, J. vom Brocke, P.-M. Léger, A. B. Randolph, & G. Müller-Putz (Eds.), Information Systems and Neuroscience (pp. 77–89). Springer International Publishing. https://doi.org/10.1007/978-3-030-88900-5_9 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

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 Using Convex 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

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. NeuroIS’2020 (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. B. Randolph, & T. Fischer (Eds.), Information Systems and Neuroscience (pp. 100–110). Springer International Publishing. https://doi.org/10.1007/978-3-030-60073-0_12 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

Chang, Y.-S., Gwizdka, J., & Zhang, Y. (2020). eHealth literacy, information sources, and health webpage reading patterns. Proceedings of the Association for Information Science and Technology, 57, e234. https://doi.org/10.1002/pra2.234 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

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

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

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., 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 (pp. 175–183). Springer International Publishing. https://doi.org/10.1007/978-3-319-67431-5_20 Cite