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. 2022 Aug 8:13:944250.
doi: 10.3389/fpsyg.2022.944250. eCollection 2022.

Culture, heritage looting, and tourism: A text mining review approach

Sandra Maria Correia Loureiro  1 , Amr Al-Ansi  2 , Hyungseo Bobby Ryu  3 , Antonio Ariza-Montes  4 , Heesup Han  5
Affiliations

Culture, heritage looting, and tourism: A text mining review approach

Sandra Maria Correia Loureiro et al. Front Psychol. .

Abstract

Tourism scholars have been devoted to exploring the significance of cultural heritage in generating economic, environmental, and social values. However, limited efforts were found to verify potential threats that demolish these values such as looting issue in the global heritage tourism industry. Therefore, this study has reviewed extant publications to demonstrate the potential emerged textual clusters discussed by previous studies. It also summarized the network distribution of articles journals and authors' affiliations to capture the mobility and diversity with a focus on the business and tourism management field. Hence, the core clusters discovered were related to heritage destruction, public access, world heritage, human rights, cultural heritage preservation, and protection of cultural heritage in the event. The results have established theoretical insights and research agendas for future tourism studies, while it determined critical drawbacks in employing technology tools including virtual reality, augmented reality, and artificial intelligence for cultural heritage preservation/protection.

Keywords: cultural heritage looting; cultural heritage preservation; heritage destruction; human rights; protection of cultural property; public access.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Documents search and selection.
FIGURE 2
FIGURE 2
Number of articles per journal.
FIGURE 3
FIGURE 3
Network of authors and countries of affiliation.
FIGURE 4
FIGURE 4
Text clustering. Only clusters with scores higher than 50 that represent concepts were considered. Score: shows the relevance value assigned to the cluster.
See this image and copyright information in PMC

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