TY - JOUR
T1 - Capturing public voices
T2 - The role of social media in heritage management
AU - Foroughi, Mahda
AU - de Andrade, Bruno
AU - Pereira Roders, A.
PY - 2023
Y1 - 2023
N2 - Social media platforms have been increasingly used by locals and tourists to express their opinions about buildings, cities, and built heritage in particular. Most recently, scholars have been using social media to conduct innovative research on built heritage and heritage management. Still, the application of artificial intelligence (AI) methods to analyze social media data for heritage management is seldom explored. This paper investigates the potentials of short texts (sentences and hashtags) shared through social media as a data source and artificial intelligence methods for data analysis for revealing the cultural significance (values and attributes) of built heritage. The city of Yazd, Iran was taken as a case study, with the particular focus on windcatchers, key attributes conveying outstanding universal values, as inscribed on the UNESCO World Heritage List. This paper has three subsequent phases: 1) state of the art on the intersection of public participation in heritage management and social media research; 2) methodology of data collection and data analysis related to coding people's voices from Instagram and Twitter into values of windcatchers over the last ten-years; 3) preliminary findings on the comparison between opinions of locals and tourists, sentiment analysis, and its association with the values and attributes of windcatchers. Results indicate that the age value is recognized as the most important value by all interest groups, while the political value is the least acknowledged. Besides, the negative sentiments are scarcely reflected (e.g., critiques) in social media. Results confirm the potential of social media for heritage management in terms of (de)coding and measuring the cultural significance of built heritage for windcatchers and also other attributes in Yazd and other case studies and scales.
AB - Social media platforms have been increasingly used by locals and tourists to express their opinions about buildings, cities, and built heritage in particular. Most recently, scholars have been using social media to conduct innovative research on built heritage and heritage management. Still, the application of artificial intelligence (AI) methods to analyze social media data for heritage management is seldom explored. This paper investigates the potentials of short texts (sentences and hashtags) shared through social media as a data source and artificial intelligence methods for data analysis for revealing the cultural significance (values and attributes) of built heritage. The city of Yazd, Iran was taken as a case study, with the particular focus on windcatchers, key attributes conveying outstanding universal values, as inscribed on the UNESCO World Heritage List. This paper has three subsequent phases: 1) state of the art on the intersection of public participation in heritage management and social media research; 2) methodology of data collection and data analysis related to coding people's voices from Instagram and Twitter into values of windcatchers over the last ten-years; 3) preliminary findings on the comparison between opinions of locals and tourists, sentiment analysis, and its association with the values and attributes of windcatchers. Results indicate that the age value is recognized as the most important value by all interest groups, while the political value is the least acknowledged. Besides, the negative sentiments are scarcely reflected (e.g., critiques) in social media. Results confirm the potential of social media for heritage management in terms of (de)coding and measuring the cultural significance of built heritage for windcatchers and also other attributes in Yazd and other case studies and scales.
KW - Artificial intelligence
KW - Cultural significance
KW - Public participation
KW - Sentiment analysis
KW - Social media
UR - http://www.scopus.com/inward/record.url?scp=85174925386&partnerID=8YFLogxK
U2 - 10.1016/j.habitatint.2023.102934
DO - 10.1016/j.habitatint.2023.102934
M3 - Article
AN - SCOPUS:85174925386
SN - 0197-3975
VL - 142
JO - Habitat International
JF - Habitat International
M1 - 102934
ER -