Utilization of Questionnaire Results Using Aspect-based Sentiment Analysis

• Published in: Procedia computer science 2022, Vol.207, p.351-359
• Main Authors: Kabasawa, Kyoko, Tsuda, Kazuhiko
• Format: Article
• Language: English
• Subjects: aspect-based sentiment analysis; sentiment analysis; text mining
• ISSN: 1877-0509; 1877-0509
• DOI: 10.1016/j.procs.2022.09.069

Often, existing sentiment analysis determines whether a questionnaire is positive or negative. Unfortunately, this makes it challenging to utilize the negative and correct them. This study used descriptive questionnaires from customers who visited Japanese gastropubs and analyzed them to determine the correct polarity. We used existing sentiment analysis methods to see if the questionnaire was not classified as the correct polarity (positive or negative). Consequently, we found that the whole sentence of the questionnaire was still not always able to judge the content and polarity correctly. Therefore, we conducted an aspect-based sentiment analysis, characterized by a polarity evaluation of certain words in a sentence, rather than a polarity evaluation of the whole sentence. Negative expressions were extracted from the text to determine what was negative. From each expression, it was possible to see what was explicitly unsatisfactory. The extracted expressions were also grouped as aspects belonging to the same group before examining them individually. Subsequently, the extracted expressions were grouped into aspects, resulting in the percentage of each aspect. The results were then used to suggest what could be improved for Japanese gastropubs.