An Annotated Turkish Aspect Based Sentiment Analysis Corpus for Smart Tourism

Abstract

In the processing of data produced by users, aspect based sentiment analysis (ABSA) studies are carried out today instead of classical sentiment analysis approaches. ABSA enables the determination of detailed feelings and thoughts for each component of the product or service in a user post. Using ABSA, it is possible to determine the weak and strong aspects of the tourism centers in line with the visitor comments about the tourist places. The concept of smart tourism has started to attract a lot of attention in recent years. Smart tourism is an artificial intelligence-based solution that offers the necessary systems for comfortable travel to visitors. Developing artificial intelligence-based solutions such as ABSA for tourism centers in Turkey, tourism centers can be turned into attractions. One of the most important tasks of ABSA is the extraction of aspect terms, that is, the extraction of tourism center features/aspects. The lack of a large-scale corpus labeled for this task in the Turkish language is one of the obstacles for researchers in this field. In this study, a new corpus has been created for smart tourism and ABSA. Moreover, visitor reviews to important tourism centers in Turkey were collected and labeled manually by seven different annotators as aspect term-sentiment pairs for ABSA. Latent Dirichlet Allocation (LDA) algorithm was used as a baseline approach for extracting aspect terms from visitor reviews. The created dataset has been uploaded to GitHub for all researchers. © 2021 IEEE.