Perception of AI-generated art: text analysis of online discussions
Zapiski Nauchnykh Seminarov POMI, Investigations on applied mathematics and informatics. Part II–1, Tome 529 (2023), pp. 6-23 Cet article a éte moissonné depuis la source Math-Net.Ru

Voir la notice du chapitre de livre

In this work we analyze comments on three subreddits related to AI-generated art to understand how people perceive the ability of AI to create art and the topics and moods of discussions in the context of widespread usage of pre-trained models. We used computational text analysis techniques such as LDA topic modeling and sentiment analysis with sentiment lexicons. As a result, we find that discussions on technical topics and descriptions of AI-generated art were mainly positive, while discussions on socio-cultural issues were mainly negative and took place in a subreddit focused on defending AI art. The findings suggest that Reddit users are interested in both the artistic and socio-cultural implications of AI-generated art, finding it risky and questionable.
@article{ZNSL_2023_529_a1,
     author = {S. Bosonogov and A. Suvorova},
     title = {Perception of {AI-generated} art: text analysis of online discussions},
     journal = {Zapiski Nauchnykh Seminarov POMI},
     pages = {6--23},
     year = {2023},
     volume = {529},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/ZNSL_2023_529_a1/}
}
TY  - JOUR
AU  - S. Bosonogov
AU  - A. Suvorova
TI  - Perception of AI-generated art: text analysis of online discussions
JO  - Zapiski Nauchnykh Seminarov POMI
PY  - 2023
SP  - 6
EP  - 23
VL  - 529
UR  - http://geodesic.mathdoc.fr/item/ZNSL_2023_529_a1/
LA  - en
ID  - ZNSL_2023_529_a1
ER  - 
%0 Journal Article
%A S. Bosonogov
%A A. Suvorova
%T Perception of AI-generated art: text analysis of online discussions
%J Zapiski Nauchnykh Seminarov POMI
%D 2023
%P 6-23
%V 529
%U http://geodesic.mathdoc.fr/item/ZNSL_2023_529_a1/
%G en
%F ZNSL_2023_529_a1
S. Bosonogov; A. Suvorova. Perception of AI-generated art: text analysis of online discussions. Zapiski Nauchnykh Seminarov POMI, Investigations on applied mathematics and informatics. Part II–1, Tome 529 (2023), pp. 6-23. http://geodesic.mathdoc.fr/item/ZNSL_2023_529_a1/

[1] R. Arun, V. Suresh, C. E. Veni Madhavan, and M. N. Narasimha Murthy, “On finding the natural number of topics with latent dirichlet allocation: Some observations”, Advances in Knowledge Discovery and Data Mining, 14th Pacific-Asia Conference, PAKDD 2010, Proceedings (Hyderabad, India, June 21-24, 2010), v. I, Springer, 2010, 391–402

[2] S. Audry, J. Ippolito, “Can artificial intelligence make art without artists? ask the viewer”, MDPI, Arts, 8, 2019, 35 pp.

[3] E. Bericat, “The sociology of emotions: Four decades of progress”, Current Sociology, 64:3 (2016), 491–513

[4] D. M. Blei, A. Y. Ng, M. I. Jordan, “Latent dirichlet allocation”, J. Mach. Learn. Research, 3, Jan (2003), 993–1022

[5] M. A. Boden, “The turing test and artistic creativity”, Kybernetes, 39:3 (2010), 409–413

[6] A. Broeckmann, “The machine as artist as myth”, MDPI, Arts, 8, 2019, 25 pp.

[7] J. Cao, T. Xia, J. Li, Y. Zhang, and S. Tang, “A density-based method for adaptive lda model selection”, Neurocomputing, 72:7–9 (2009), 1775–1781

[8] R. Chamberlain, C. Mullin, B. Scheerlinck, J. Wagemans, “Putting the art in artificial: Aesthetic responses to computer-generated art”, Psychology of Aesthetics, Creativity, and the Arts, 12:2 (2018), 177

[9] R. Deveaud, E. SanJuan, and P. Bellot, “Accurate and effective latent concept modeling for ad hoc information retrieval”, Document numérique, 17:1 (2014), 61–84

[10] P. DiMaggio, E. Hargittai, W. R. Neuman, J. P. Robinson, “Social implications of the internet”, Annual Review of Sociology, 27:1 (2001), 307–336

[11] G. Eysenbach, J. E, Till, “Ethical issues in qualitative research on internet communities”, Bmj, 323:7321 (2001), 1103–1105

[12] M. R. Frank, D. Autor, J. E. Bessen, E. Brynjolfsson, M. Cebrian, D. J. Deming, M. Feldman, M. Groh, J. Lobo, E. Moro, et al., “Toward understanding the impact of artificial intelligence on labor”, Proceedings of the National Academy of Sciences, 116:14 (2019), 6531–6539

[13] T. L. Griffiths, M. Steyvers, “Finding scientific topics”, Proceedings of the National academy of Sciences, 101, suppl_1 (2004), 5228–5235

[14] B. Guo, X. Zhang, Z. Wang, M. Jiang, J. Nie, Y. Ding, J. Yue, and Y. Wu, How close is chatgpt to human experts? comparison corpus, evaluation, and detection, 2023, arXiv: 2301.07597

[15] L. K. Hansen, A. Arvidsson, F. Nielsen, E. Colleoni, M. Etter, “Good friends, bad news-affect and virality in twitter”, Future Information Technology, 6th International Conference, FutureTech 2011, Proceedings (Loutraki, Greece, June 28-30, 2011), v. II, Springer, 2011, 34–43

[16] M. Ul Haque, I. Dharmadasa, Z. T. Sworna, R. N. Rajapakse, H. Ahmad, " i think this is the most disruptive technology": Exploring sentiments of chatgpt early adopters using twitter data, 2022, arXiv: 2212.05856

[17] A. Hertzmann, Can computers create art?, MDPI, Arts, 7, 2018, 18 pp.

[18] J.-Wha Hong, Nathaniel Ming Curran, “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 (2019), 1–16

[19] T. Leshkevich, A. Motozhanets, “Social perception of artificial intelligence and digitization of cultural heritage: Russian context”, Applied Sciences, 12:5 (2022), 2712

[20] M. Mazzone, A. Elgammal, “Art, creativity, and the potential of artificial intelligence”, MDPI, Arts, 8, 2019, 26 pp.

[21] J. McCormack, T. Gifford, P. Hutchings, “Autonomy, authenticity, authorship and intention in computer generated art”, International conference on computational intelligence in music, sound, art and design (part of EvoStar), Springer, 2019, 35–50

[22] A. Pannu, “Artificial intelligence and its application in different areas”, Artificial Intelligence, 4:10 (2015), 79–84

[23] A. Park, M. Conway, A. T. Chen, “Examining thematic similarity, difference, and membership in three online mental health communities from reddit: a text mining and visualization approach”, Computers in human behavior, 78 (2018), 98–112

[24] M. Ragot, N. Martin, S. Cojean, Ai-generated vs. human artworks. a perception bias towards artificial intelligence?, Extended abstracts of the 2020 CHI conference on human factors in computing systems, 2020, 1–10

[25] SberUniversity and GeekBrains, Managing changes in education: Generative ai., 2023

[26] V. S. Shirsat, R. S. Jagdale, S. N. Deshmukh, “Sentence level sentiment identification and calculation from news articles using machine learning techniques”, Computing, Communication and Signal Processing, Proceedings of ICCASP 2018, Springer, 2019, 371–376

[27] S. Taj, B. B. Shaikh, A. F. Meghji, “Sentiment analysis of news articles: A lexicon based approach”, 2019 2nd international conference on computing, mathematics and engineering technologies (iCoMET), IEEE, 2019, 1–5

[28] P. A. Thoits, “The sociology of emotions”, Annual Review of Sociology, 15:1 (1989), 317–342

[29] S.-C. Yeh, A.-W. Wu, H.-C. Yu, H. C. Wu, Y.-P. Kuo, and P.-X. Chen, “Public perception of artificial intelligence and its connections to the sustainable development goals”, Sustainability, 13:16 (2021), 9165

[30] C. Zhang, Y. Lu, “Study on artificial intelligence: The state of the art and future prospects”, J. Industr. Inform. Integration, 23 (2021), 100224