A Social Recommendation Framework for Chinese Long-stayers in Chiang Mai
Die Hu, Danaitun Pongpatcharatrontep, Sirikorn Santirojanakul, Achara Khamaksorn · 2022 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON) · 2022
With the tremendous development of the Internet, e-commerce and social networks, research on Social Recommendation Systems has become a hot topic to solve information overload and respond to diverse individual demands. However, many of the existing social recommendation methods lack an in-depth analysis of long-stay users from cross-cultural backgrounds, which causes insufficient social recommendations, since the social attributes and requirements of these users differ from those of short-stay tourists, local organisations or residents. Therefore, taking Chinese long-stayers in Chiang Mai as a case study, this paper follows the Knowledge Management process with the aim of producing a social recommendation framework based on social networks to provide Chinese long-stayers with filtered and efficient social recommendations. The research employs qualitative and quantitative methods to investigate the research problems and conducts online surveys and in-depth interviews to collect the individual and collective data and analyse them using Social Network Analysis. The proposed social recommendation framework aims to benefit Chinese long-stayers and any other organisations that need social recommendations or innovative business and management strategies in relation to Chinese long-stayers in Chiang Mai. The preliminary work will contribute to the current accumulative knowledge of the impact of social networks of Chinese long-stayers on social recommendation performance in a cross-cultural context.