Sentiment Analysis of Cultural Heritage Landscape Elements Using Big Data of Online Comments: A Case Study of the Humble Administrator’s Garden in China
- DOI
- 10.2991/978-94-6463-034-3_7How to use a DOI?
- Keywords
- Historical landscape; landscape perception; big data; cultural heritage
- Abstract
The big data of online comments has been widely used in fields, however, few research on sentiment of cultural heritage conducted. This study explores the sentiment of tourists about the Humble Administrator’s Garden using big data of online comments in Ctrip and Qiongyou websites. Word frequency analysis was used to extract the landscape elements and cluster and sentiment analysis were conducted for landscape elements sets. Sentiment analysis was calculated by model of l(w) = n(w) a(w) s(w) m(w). The study shows eight sets of landscape elements interested by tourists exist, in which humanities elements and water related are most considered. The positive sentiment of these two sets is more than 88%, while visiting service is only 69% and stone is 70%. The study provides a supporting attempt of online comment data in the field of cultural heritage, which contributes to the improvement of management and conservation towards the cultural heritage landscape.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Qianda Zhuang AU - Shuzhen Chen PY - 2022 DA - 2022/12/23 TI - Sentiment Analysis of Cultural Heritage Landscape Elements Using Big Data of Online Comments: A Case Study of the Humble Administrator’s Garden in China BT - Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022) PB - Atlantis Press SP - 48 EP - 56 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-034-3_7 DO - 10.2991/978-94-6463-034-3_7 ID - Zhuang2022 ER -