Topic Modeling for Analyzing Topic Manipulation Skills

• Main Authors: Seok-Ju Hwang, Yoon-Kyoung Lee, Jong-Dae Kim, Chan-Young Park, Yu-Seop Kim
• Format: Article
• Language: English
• Published: MDPI AG 2021-08-01
• Series: Information
• Subjects: LDA; Doc2Topic; topic modeling; topic manipulation skills analysis
• Online Access: https://www.mdpi.com/2078-2489/12/9/359

There are many ways to communicate with people, the most representative of which is a conversation. A smooth conversation should not only be written in a grammatically appropriate manner, but also deal with the subject of conversation; this is known as language ability. In the past, this ability has been evaluated by language analysis/therapy experts. However, this process is time-consuming and costly. In this study, the researchers developed a Hallym Systematic Analyzer of Korean language to automate the conversation analysis process traditionally conducted by language analysis/treatment experts. However, current morpheme analyzers or parsing analyzers can only evaluate certain elements of a conversation. Therefore, in this paper, we added the ability to analyze the topic manipulation skills (the number of topics and the rate of topic maintenance) using the existing Hallym Systematic Analyzer of Korean language. The purpose of this study was to utilize the topic modeling technique to automatically evaluate topic manipulation skills. By quantitatively evaluating the topic management capabilities that were previously evaluated in a conventional manner, it was possible to automatically analyze language ability in a wider range of aspects. The experimental results show that the automatic analysis methodology presented in this study achieved a very high level of correlation with language analysis/therapy professionals.