1 |
Belke, B., Leder, H., & Carbon, C. C. (2015). When challenging art gets liked: Evidences for a dual preference formation process for fluent and non-fluent portraits. PloS one, 10(8), e0131796.
DOI
|
2 |
Berlyne, D. E. (1970). Novelty, complexity, and hedonic value. Perception & Psychophysics, 8(5-A), 279-286.
DOI
|
3 |
Boselie, F. (1991). Against prototypicality as a central concept in aesthetics. Empirical Studies of the Arts, 9(1), 65-73.
DOI
|
4 |
Martindale, C. & Moore, K. (1988). Priming, prototypicality, and preference. Journal of Experimental Psychology: Human Perception and Performance, 14(4), 661.
DOI
|
5 |
Mastandrea, S., Bartoli, G., & Bove, G. (2009). Preferences for ancient and modern art museums: Visitor experiences and personality characteristics. Psychology of Aesthetics, Creativity, and the Arts, 3(3), 164-173.
DOI
|
6 |
Chatterjee A., Widick P., Sternschein R., Smith W. B., & Bromberger B. (2010). The assessment of art attributes. Empirical Studies of Arts, 28(2), 207-222.
DOI
|
7 |
Flexas, A., Rossello, J., de Miguel, P., Nadal, M., & Munar, E. (2014). Cognitive control and unusual decisions about beauty: An fMRI study. Frontiers in Human Neuroscience, 8(520), 1-9.
|
8 |
Gangadharbatla, H. (2021). The role of ai attribution knowledge in the evaluation of artwork. Empirical Studies of the Arts, 40(2), 125-142.
DOI
|
9 |
Elgammal, A., Liu, B., Elhoseiny, M., & Mazzone, M. (2017). Can: Creative adversarial networks, generating "art" by learning about styles and deviating from style norms. arXiv Preprint arXiv: 1706.07068.
|
10 |
Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191.
DOI
|
11 |
Hong, J. W. & Curran, N. M. (2019). Artificial intelligence, artists, and art: Attitudes toward artwork produced by humans vs. artificial intelligence. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 15(2s), 1-16.
|
12 |
Huang, M., Bridge, H., Kemp, M. J., & Parker, A. J. (2011). Human cortical activity evoked by the assignment of authenticity when viewing works of art. Frontiers in Human Neuroscience, 5(134), 1-9.
|
13 |
Jakesch, M. & Leder, H. (2009). Finding meaning in art: Preferred levels of ambiguity in art appreciation. Quarterly Journal of Experimental Psychology, 62(11), 2105-2112.
DOI
|
14 |
Kirk, U., Skov, M., Hulme, O., Christensen, M. S., & Zeki, S. (2009). Modulation of aesthetic value by semantic context: An fMRI study. NeuroImage, 44(3), 1125-1132.
DOI
|
15 |
Leder, H., Carbon, C. C., & Ripsas, A. L. (2006). Entitling art: Influence of title information on understanding and appreciation of paintings. Acta Psychologica, 121(2), 176-198.
DOI
|
16 |
Leder, H., & Nadal, M. (2014). Ten years of a model of aesthetic appreciation and aesthetic judgments: The aesthetic episode - Developments and challenges in empirical aesthetics. British Journal of Psychology, 105(4), 443-446.
DOI
|
17 |
Feist, G. J. & Brady, T. R. (2004). Openness to experience, non-conformity, and the preference for abstract art. Empirical Studies of the Arts, 22(1), 77-89.
DOI
|
18 |
Brainard, D. H. (1997). The psychophysics toolbox. Spatial Vision, 10(4), 433-436.
DOI
|
19 |
Bernberg, R. E. (1953). Prestige suggestion in art as communication. The Journal of Social Psychology, 38(1), 23-30.
DOI
|
20 |
Dearden, P. (1984). Factors influencing landscape preferences: An empirical investigation. Landscape Planning, 11(4), 293-306.
DOI
|
21 |
Yoon, Y. & Lee, S. (2016). Does the preference for emotional paintings depends on personality?. Science of Emotion and Sensibility, 19(3), 15-26.
DOI
|
22 |
Silveira, S., Fehse, K., Vedder, A., Elvers, K., & Hennig-Fastm K. (2015). Is it the picture or is it the frame? An fMRI study on the neurobiology of framing effects. Frontiers in Human Neuroscience, 9, 528.
|
23 |
Song, J., Kwak, Y., & Kim, C.-Y. (2021). Familiarity and novelty in aesthetic preference: The effects of the properties of the artwork and the beholder. Frontiers in Psychology, 12.
|
24 |
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich A. (2015). Going deeper with convolutions. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1-9.
|
25 |
Leder, H., Belke, B., Oeberst, A., & Augustin, D. (2004). A model of aesthetic appreciation and aesthetic judgments. British Journal of Psychology, 95(4), 489-508.
DOI
|
26 |
Gergen, K. J. & Breger, I. (1965). Two forms of inference and problems in the assessment of creativity. In Proceedings of the Annual Convention of the American Psychological Association, 215-216.
|
27 |
Hekkert, P. & Van Wieringen, P. C. (1990). Complexity and prototypicality as determinants of the appraisal of cubist paintings. British Journal of Psychology, 81(4), 483-495.
DOI
|
28 |
Isham, E. A., Ekstrom, A. D., & Banks, W. P. (2010). Effects of youth authorship on the appraisal of paintings. Psychology of Aesthetics, Creativity, and the Arts, 4(4), 235.
DOI
|
29 |
Lee, K. & Ashton, M. C. (2004). Psychometric properties of the HEXACO personality inventory. Multivariate Behavioral Research, 39(2), 329-358.
DOI
|
30 |
Mordvintsev, A., Olah, C., & Tyka, M. (2015). Inceptionism: going deeper into neural networks. Retrieved from http://googleresearch.blogspot.com/2015/06/inceptionism-going-deeper-into-neural.html.
|
31 |
Muth, C. & Carbon, C. C. (2013). The aesthetic aha: On the pleasure of having insights into Gestalt. Acta Psychologica, 144(1), 25-30.
DOI
|
32 |
Newman, G. E. & Bloom, P. (2012). Art and authenticity: The importance of originals in judgments of value. Journal of Experimental Psychology: General, 141(3), 558-569.
DOI
|
33 |
Ragot, M., Martin, N., & Cojean, S. (2020). Ai-generated vs. human artworks. a perception bias towards artificial intelligence? In Extended abstracts of the 2020 CHI conference on human factors in computing systems (pp. 1-10).
|
34 |
Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics. Spatial Vision, 10, 437-442.
DOI
|