설득적 에세이 점수의 예측도구로서의 감성분석 기법

• 영문명: Sentiment Analysis as a Predictor for Scores of Persuasive Essays
• 발행기관: 한국교원대학교 뇌·AI기반교육연구소
• 저자명: 신동광(Dongkwang Shin)
• 간행물 정보: 『Brain, Digital, & Learning』제11권 제2호, 215~226쪽, 전체 12쪽
• 주제분류: 사회과학 > 교육학
• 파일형태: PDF
• 발행일자: 2021.06.30

영문 초록

This study aimed to investigate to what extent sentiment analysis can be applied to tone analysis of persuasive essays as a predictor for scores of the essays. To this end, the sentiment analysis of the text mining program ‘Orange3’ was utilized. This study first looked at the effects of Vader s sentiment indices (positive, negative, neutral, and compound values) on the total score of positive and negative essays. As a result, in the positive essay, all the sentiment analysis results had a significant effect on the total score. In particular, it was confirmed that the compound value had the greatest influence as a predictor of the total score of the positive essay as well as the scores in the four sub-scoring domains—task performance, content, organization and language use. On the other hand, it turned out that there were no significant relationship between sentiment indices and scores of negative essays. These results suggest that even if learners write a persuasive essay with either positive or negative tone, they could expect a higher score when comparing the two opposite positions rather than the one-sided one. This was also confirmed to some extent through word cloud analysis. Of course, there were some limitations in this study as well but it showed the applicability of sentiment analysis to predict scores of persuasive essays.

목차

Introduction

Theoretical Background

Methods

Results and Discussion

Conclusion and Implications

References

키워드

Sentiment analysis Orange3 persuasive essay argument mining word cloud