Determining how to assess public interests and include the public’s ideas in heritage protection has become a technical issue, but relevant research still remains limited. This chapter aims to test the digital footprints of social media users as a public participatory tool, with the objectives of identifying industrial heritage landscape attributes and assessing associated values. Targeting the Sanxian industrial heritage landscape of Liangdancheng in China as a case study, in this chapter, the data from user-generated content on social media platforms Ctrip, Weibo, and Meituan were collected and processed with ROST CM 6 and NVivo 12, and content analysis (CA) and importance-performance analysis (IPA) were conducted. Results revealed that the industrial heritage landscape of Liangdancheng encompasses various built, cultural, and natural environmental resources, including both tangible and intangible attributes. These attributes were assessed and categorised into four quadrants of importance-performance characteristics, wherein cultural environmental resources show relatively high performance but built environmental resources need further actions to improve their value perception and interpretation among the public. This research demonstrated that the digital footprints of social media users as a participatory tool can work well in terms of data accessibility, value identification, and public representation, advancing the theoretical framework of Chinese industrial heritage management and global practices.

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Digital Footprint as a Public Participatory Tool: Identifying and Assessing Industrial Heritage Landscape Through User-Generated Content on Social Media

  • Ji Li

摘要

Determining how to assess public interests and include the public’s ideas in heritage protection has become a technical issue, but relevant research still remains limited. This chapter aims to test the digital footprints of social media users as a public participatory tool, with the objectives of identifying industrial heritage landscape attributes and assessing associated values. Targeting the Sanxian industrial heritage landscape of Liangdancheng in China as a case study, in this chapter, the data from user-generated content on social media platforms Ctrip, Weibo, and Meituan were collected and processed with ROST CM 6 and NVivo 12, and content analysis (CA) and importance-performance analysis (IPA) were conducted. Results revealed that the industrial heritage landscape of Liangdancheng encompasses various built, cultural, and natural environmental resources, including both tangible and intangible attributes. These attributes were assessed and categorised into four quadrants of importance-performance characteristics, wherein cultural environmental resources show relatively high performance but built environmental resources need further actions to improve their value perception and interpretation among the public. This research demonstrated that the digital footprints of social media users as a participatory tool can work well in terms of data accessibility, value identification, and public representation, advancing the theoretical framework of Chinese industrial heritage management and global practices.