| Title |
Identifying Criteria Points for Architectural Aesthetic Levels in Public Buildings and Analyzing Emotional Texts |
| Authors |
이동주(Lee, Dong-Joo) ; 고은형(Ko, Eun-Hyung) |
| DOI |
https://doi.org/10.5659/JAIK.2024.40.8.3 |
| Keywords |
Beauty; Architectural Aesthetic; Emotion; Text Analysis; Big-data |
| Abstract |
This study aims to identify the relationship between the level of architectural aesthetic and the sensibility of architectural aesthetic. The main findings from analyzing architectural aesthetic criteria points, word clouds, TF-IDF, and sentiment analysis on text data from 1,775 survey responses revealed several insights. Architectural aesthetic was categorized into three stages based on criteria points: a negative word-centered section below 35 points, an increasing aesthetic score section between 35 and 65 points, and a high aesthetic score section above 65 points. Word cloud analysis identified that negative perceptions of construction and issues with harmony were the primary factors reducing architectural aesthetic. Conversely, nature-friendliness and visual artistic inspiration were factors that increased aesthetic scores. TF-IDF analysis highlighted two major design factors with high scores. The first was eco-friendly/nature-friendly elements, and the second was emotions that evoke new, visually surprising, or shocking experiences. Finally, sentiment analysis showed that as the level of architectural aesthetic increased, negative emotional vocabulary decreased, while positive emotional vocabulary increased. To conduct a more detailed emotional analysis of architectural aesthetic, developing a specialized emotional dictionary encompassing various architectural sensibilities is necessary. |