Araştırma Makalesi

AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS

Cilt: 20 Sayı: ICMEB'24 Özel Sayı 30 Ekim 2024
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AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS

Öz

The generative AI concept, which enables users to create text, image, and video content through prompts, is revolutionizing the content side and AI applications in marketing. Despite the increasing popularity of generative AI applications, the market perception regarding generative AI remains underexplored. This study aims to explore the generative AI market perception through the context of mobile applications with the help of user reviews. The study follows a structured approach including identifying the generative AI mobile applications, assessing the context through rating scores and install amounts of mobile applications, and using a topic modeling approach (BerTopic) for online reviews to identify the topics included in the conversation. 8159 user reviews from 22 mobile applications are used as sample of the study and the average rating score for the sample found as 4,06 which signals a positive perception of market. The study concludes top ten topics as; “Dissatisfaction About Amount of Advertisements in app”, “NSFW Content and Moderation”, “Praise of Application”, “Functionality Problems & Crashes”, “Payment Necessity and Trial Problems”, “In-App Purchase Restoration Problems”, “Specific Feature in App”, “Chat Function”, “Credit System” and “Excess of Ads”. The study reveals the main issues of Ai Art mobile applications for marketing decision-making processes.

Anahtar Kelimeler

Kaynakça

  1. Ali, S., DiPaola, D., Lee, I., Sindato, V., Kim, G., Blumofe, R., & Breazeal, C. (2021). Children as creators, thinkers and citizens in an AI-driven future. Computers and Education: Artificial Intelligence, 2, 1-11.
  2. Allsop, D. T., Bassett, B. R., & Hoskins, J. A. (2007). Word-of-mouth research: Principles and applications. Journal of Advertising Research, 47(4), 398-411.
  3. Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., Suh, J., Iqbal, S., Bennett, P.N., Inkpen, K.M., Teevan, J., Kikin-Gil, R., & Horvitz, E. (2019). Guidelines for human-AI interaction. In Proceedings of The 2019 Chi Conference on Human Factors in Computing Systems, (1-13), Scotland.
  4. Araci, D. (2019). Finbert: Financial sentiment analysis with pre-trained language models. arXiv preprint arXiv:1908.10063.
  5. Barbosa, R. R. L., Sánchez-Alonso, S., & Sicilia-Urban, M. A. (2015). Evaluating hotels rating prediction based on sentiment analysis services. Aslib Journal of Information Management, 67(4), 392-407.
  6. Berezina, K., Bilgihan, A., Cobanoglu, C., & Okumus, F. (2016). Understanding satisfied and dissatisfied hotel customers: Text mining of online hotel reviews. Journal of Hospitality Marketing & Management, 25(1), 1-24.
  7. Bickart, B., & Schindler, R. M. (2001). Internet forums as influential sources of consumer information. Journal of Interactive Marketing, 15(3), 31-40.
  8. Cao, Q., Duan, W., & Gan, Q. (2011). Exploring determinants of voting for the “helpfulness” of online user reviews: A text mining approach. Decision Support Systems, 50(2), 511-521.

Ayrıntılar

Birincil Dil

İngilizce

Konular

İş Sistemleri (Diğer)

Bölüm

Araştırma Makalesi

Erken Görünüm Tarihi

24 Ekim 2024

Yayımlanma Tarihi

30 Ekim 2024

Gönderilme Tarihi

8 Haziran 2024

Kabul Tarihi

18 Eylül 2024

Yayımlandığı Sayı

Yıl 2024 Cilt: 20 Sayı: ICMEB'24 Özel Sayı

Kaynak Göster

APA
Pınarbaşı, F. (2024). AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS. Uluslararası Yönetim İktisat ve İşletme Dergisi, 20(ICMEB’24 Özel Sayı), 101-113. https://doi.org/10.17130/ijmeb.1498188
AMA
1.Pınarbaşı F. AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS. ijmeb. 2024;20(ICMEB’24 Özel Sayı):101-113. doi:10.17130/ijmeb.1498188
Chicago
Pınarbaşı, Fatih. 2024. “AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS”. Uluslararası Yönetim İktisat ve İşletme Dergisi 20 (ICMEB’24 Özel Sayı): 101-13. https://doi.org/10.17130/ijmeb.1498188.
EndNote
Pınarbaşı F (01 Ekim 2024) AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS. Uluslararası Yönetim İktisat ve İşletme Dergisi 20 ICMEB’24 Özel Sayı 101–113.
IEEE
[1]F. Pınarbaşı, “AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS”, ijmeb, c. 20, sy ICMEB’24 Özel Sayı, ss. 101–113, Eki. 2024, doi: 10.17130/ijmeb.1498188.
ISNAD
Pınarbaşı, Fatih. “AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS”. Uluslararası Yönetim İktisat ve İşletme Dergisi 20/ICMEB’24 Özel Sayı (01 Ekim 2024): 101-113. https://doi.org/10.17130/ijmeb.1498188.
JAMA
1.Pınarbaşı F. AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS. ijmeb. 2024;20:101–113.
MLA
Pınarbaşı, Fatih. “AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS”. Uluslararası Yönetim İktisat ve İşletme Dergisi, c. 20, sy ICMEB’24 Özel Sayı, Ekim 2024, ss. 101-13, doi:10.17130/ijmeb.1498188.
Vancouver
1.Fatih Pınarbaşı. AI ART IN MOBILE: TOPIC MODELING OF USER REVIEWS FOR GENERATIVE AI APPLICATIONS. ijmeb. 01 Ekim 2024;20(ICMEB’24 Özel Sayı):101-13. doi:10.17130/ijmeb.1498188


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