Analyzing the perception differences and influencing factors of cross-cultural groups in heritage tourism can help heritage sites to formulate differentiated service and improve tourist satisfaction. This research adopted the BERT model to undertake sentiment analysis of 17,555 Chinese online reviews for nine scenic spots in Melaka. Using vocabulary filtering, co-occurrence analysis, and semantic clustering technology, the emotional characteristics of Chinese outbound tourists when they visited heritage sites in Melaka were analyzed, which revealed the factors influencing their positive and negative emotions. Results showed that: 1. The BERT-based deep learning approach can obtain improved sentiment predictive performance. 2. Chinese tourists’ general emotional perceptions of Melaka were positive and they were very interested in heritage sites. 3. The most important reason for the negative emotions of Chinese tourists was a lack of cultural experience in Melaka. This research expands the application of deep learning in the field of tourism, and it helps heritage tourism destinations to improve their marketing plans for Chinese tourists and achieve long-term sustainable development of the destination.

Travel digital footprints can be used to analyze tourists’ spatio-temporal behavior to customize travel plans and recommendations. This study focuses on Chinese tourists in Malaysia as the research subject and uses the tourism digital footprint of Chinese tourists’ travel texts on Qunar.com as the primary data source. It connects traditional quantitative analysis with complex network analysis to study tourists’ behavior, time pattern, and complex network effects. The research results were as follows: (1) there was an uneven distribution of core tourism nodes with structural holes in Malaysia, which form a network pattern of imbalanced power and fierce internal competition; (2) the digital footprints of Chinese tourists were mainly concentrated in traditional tourist hot spots in Malaysia; (3) besides the competition between domestic islands, Thailand and Singapore are Malaysia’s main competitors for Chinese tourists. Based on the above research results, this paper proposes the following suggestions: (1) support the emerging or potential tourist destinations vigorously based on consolidating the existing traditional tourist cities; (2) allow core cities to play the full role of actively attracting tourists to transfer to next-level destinations; (3) to conduct digital precision marketing by relying on the tourists’ consumption behavior big data; (4) integrate regional resources, refine the tourism market, and develop characteristic tourism products differently.

Purpose The present study explored the association between witnessing parental Intimate partner violence (IPV) and cyberbullying perpetration in emerging adulthood. Furthermore, a chain-mediated model was tested to examine the roles of self-differentiation and core self-evaluation in this relationship. Methods A total of 1,186 Chinese college students (M_age = 19.59, SD = 1.32; 540 males, 646 females) completed self-report measures of parental IPV, self-differentiation, core self-evaluation, and cyberbullying perpetration. SPSS 25.0 was used to evaluate self-differentiation and core self-evaluation as chain-mediators of the direct and indirect relationships between witnessing parental IPV and cyberbullying perpetration in emerging adulthood. Results The findings revealed that emerging adults who experienced parental IPV were more likely to engage in cyberbullying toward others. This relationship was sequentially mediated by self-differentiation and core self-evaluation. Conclusions Our study revealed how witnessing parental IPV is related to cyberbullying perpetration in emerging adulthood and the underlying mechanisms involved. These insights provide new viewpoints on how witnessing parental IPV influences cyberbullying perpetration among emerging adults in the digital age and highlight the importance of addressing issues of self-differentiation and core self-evaluation in intervention strategies.