Abstract
The recent surge in AI advancements, particularly generative AI, has grabbed the attention of major tech companies who are all striving to integrate it seamlessly into their products. This highlights the need to evaluate the various AI products on the market and identify the features that resonate most with users. SAS Enterprise Miner, a powerful text analysis tool, can be used to uncover hidden insights from user reviews. In this study, we will leverage various SAS functions to analyze reviews of different AI applications. By analyzing these reviews, we aim to pinpoint the unique strengths of these AI applications and propose improvements for existing ones. Furthermore, we hope to shed light on the potential social and economic impacts of these advancements based on our findings.
Recommended Citation
Chowdhury, I. K., & Yu, W. B. (2024). Information Extraction from the Reviews of Ai Applications using Sas Text Mining Process. Issues in Information Systems, 25(4), pp. 127-135. International Association for Computer Information Systems.
The definitive version is available at https://doi.org/10.48009/4_iis_2024_110
Department(s)
Business and Information Technology
Keywords and Phrases
AI products; customer reviews; feature extraction; information retrieval; SAS Enterprise Miner; text mining
International Standard Serial Number (ISSN)
1529-7314
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 International Association for Computer Information Systems, All rights reserved.
Publication Date
01 Jan 2024
