Towards an enhanced aspect-based contradiction detection approach for online review content

• Main Authors: Azman, Siti Nuradilah, Ishak, Iskandar, Sharef, Nurfadhlina Mohd, Sidi, Fatimah
• Format: Article
• Language: English
• Published: IOP Publishing 2017
• Online Access: http://psasir.upm.edu.my/id/eprint/63587/1/Towards%20an%20Enhanced%20Aspect-based%20Contradiction%20Detection.pdf; http://psasir.upm.edu.my/id/eprint/63587/; http://iopscience.iop.org/article/10.1088/1742-6596/892/1/012006/pdf
• Institution: Universiti Putra Malaysia

User generated content as such online reviews plays an important role in customer’s purchase decisions. Many works have focused on identifying satisfaction of the reviewer in social media through the study of sentiment analysis (SA) and opinion mining. The large amount of potential application and the increasing number of opinions expresses on the web results in researchers interest on sentiment analysis and opinion mining. However, due to the reviewer’s idiosyncrasy, reviewer may have different preferences and point of view for a particular subject which in this case hotel reviews. There is still limited research that focuses on this contradiction detection in the perspective of tourism online review especially in numerical contradiction. Therefore, the aim of this paper to investigate the type of contradiction in online review which mainly focusing on hotel online review, to provide useful material on process or methods for identifying contradiction which mainly on the review itself and to determine opportunities for relevant future research for online review contradiction detection. We also proposed a model to detect numerical contradiction in user generated content for tourism industry.