Contents of the JASIS&T special issue on Neuro-Information Science.
To see the special issue on Wiley’s website click here.
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List of articles:
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Jones, L. M., Wright, K. D., Jack, A. I., Friedman, J. P., Fresco, D. M., Veinot, T., Lu, W., & Moore, S. M. (2019). The relationships between health information behavior and neural processing in african americans with prehypertension. Journal of the Association for Information Science and Technology, 0(0). https://doi.org/10.1002/asi.24098 Cite
Kim, H. H., & Kim, Y. H. (2019). ERP/MMR Algorithm for Classifying Topic-Relevant and Topic-Irrelevant Visual Shots of Documentary Videos. Journal of the Association for Information Science and Technology, 0(0). https://doi.org/10.1002/asi.24179 Cite
Jacucci, G., Barral, O., Daee, P., Wenzel, M., Serim, B., Ruotsalo, T., Pluchino, P., Freeman, J., Gamberini, L., Kaski, S., & Blankertz, B. (2019). Integrating neurophysiologic relevance feedback in intent modeling for information retrieval. Journal of the Association for Information Science and Technology, 70(9), 917–930. https://doi.org/10.1002/asi.24161 Cite
Moshfeghi, Y., & Pollick, F. E. (2019). Neuropsychological model of the realization of information need. Journal of the Association for Information Science and Technology, 70(9), 954–967. https://doi.org/10.1002/asi.24242 Cite
Wu, Y., Liu, Y., Tsai, Y.-H. R., & Yau, S.-T. (2019). Investigating the role of eye movements and physiological signals in search satisfaction prediction using geometric analysis. Journal of the Association for Information Science and Technology, 70(9), 981–999. https://doi.org/10.1002/asi.24240 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
Xu, C., & Zhang, Q. (2019). The dominant factor of social tags for users’ decision behavior on e‐commerce websites: Color or text. Journal of the Association for Information Science and Technology. https://doi.org/10.1002/asi.24118 Cite