A Study on the Influencing Factors of Social Media in the Communication of Cultural Heritage Education: A Systematic Literature Review

This study examined the impact of social media on disseminating cultural heritage education. After reviewing two databases, 29 articles met our inclusion criteria. This study found that social media can expand the educational scope of cultural heritage and increase public awareness and interest in cultural heritage tourism sites and museums. However, social media is only a publicity channel. It is necessary to consider five influencing factors in social media: the subject of information distribution, the motivation of distribution, the purpose of distribution, the content of distribution, and the method of distribution, and to analyze the specific practices of social media in disseminating cultural heritage education. Therefore, more research is needed to explore the influence of social media on cultural heritage education dissemination, to explore the educational nature of social media in cultural heritage education communication, and to provide a theoretical basis for social media to promote cultural heritage education dissemination

Sensing the Cultural Significance with AI for Social Inclusion

Social Inclusion has been growing as a goal in heritage management. Whereas the 2011 UNESCO Recommendation on the Historic Urban Landscape (HUL) called for tools of knowledge documentation, social media already functions as a platform for online communities to actively involve themselves in heritage-related discussions. Such discussions happen both in “baseline scenarios” when people calmly share their experiences about the cities they live in or travel to, and in “activated scenarios” when radical events trigger their emotions. To organize, process, and analyse the massive unstructured multi-modal (mainly images and texts) user-generated data from social media efficiently and systematically, Artificial Intelligence (AI) is shown to be indispensable. This thesis explores the use of AI in a methodological framework to include the contribution of a larger and more diverse group of participants with user-generated data. It is an interdisciplinary study integrating methods and knowledge from heritage studies, computer science, social sciences, network science, and spatial analysis. AI models were applied, nurtured, and tested, helping to analyse the massive information content to derive the knowledge of cultural significance perceived by online communities. The framework was tested in case study cities including Venice, Paris, Suzhou, Amsterdam, and Rome for the baseline and/or activated scenarios. The AI-based methodological framework proposed in this thesis is shown to be able to collect information in cities and map the knowledge of the communities about cultural significance, fulfilling the expectation and requirement of HUL, useful and informative for future socially inclusive heritage management processes