“…Researchers mainly used the content-based information (e.g., words, pictures), network structure (e.g., user interaction, connectivity, temporal dynamics) and contextual aspects (e.g., geo-location) from the social media platforms to draw their conclusions in activated scenarios (Aggarwal, 2011), mainly from Twitter due to its timeliness and low time lag for updates (Williams et al, 2017). Natural language processing tools such as sentiment analysis and topic models were applied to mine the public opinions of heritage properties triggered by events (Gabrielli et al, 2014;Taecharungroj and Mathayomchan, 2019;Monteiro et al, 2014;Fukui and Ohe, 2019;Claster et al, 2010;Chaabani et al, 2018), and graphs/networks were constructed to find out the community structures (Williams et al, 2017;Barbagallo et al, 2012), critical influencers (Barbagallo et al, 2012;Campillo-Alhama and Martinez-Sala, 2019), popular destinations (Gabrielli et al, 2014), and to make personalized recommendations (Amato et al, 2016;Battiato et al, 2016). However, none of the presented studies in Table 1 have applied or developed heritage-specific tools targeted at revealing cultural significance, i.e., values and attributes of heritage properties, which should become an important initial step for the proposed framework (Bai et al, 2021).…”