Akademik Veri Yönetim Sistemi
PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, cilt.29, ss.220-229, 2023 (ESCI)
Purchasing decisions in e-commerce shopping websites are highly influenced by online reviews. Although online reviews contain fine-grained consumers' opinions that reflect their preferences towards products; an important challenge, is that the number of online reviews can be very huge for fast and effective analysis. Hence, discovering the thematic structure of documents plays an important role in analyzing online reviews. The proposed system in this paper aims to discover the main consumer interests in online reviews on Turkish e-commerce websites. For this aim, a novel hybrid method combining Latent Dirichlet Allocation (LDA) and word2vec is proposed. Finally, we compare the performance of our work with those of several state-of-the -art baselines on 7 datasets collected from well-known Turkish e -commerce websites. The experimental results show how our proposed approach was able to provide significantly improved performance over baselines. Besides, our method enables us to discover very specific topics complying with consumer interests.