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Cancer patients are important medical tourists, but data on their experiences throughout medical travel is rare. Therefore, their experiences and concerns have always been issues that researchers and managers attach great importance to. Python was used to analyze the network texts of cancer medical tourists’ experiences, and eight topics concerned by cancer medical tourists were obtained. Then the weight of each topic was calculated by the TF-IDF algorithm and a model was proposed. The results show that cancer patients pay the most attention to the medical service quality, but paid less attention to tourism involvement. Emotional support is an important dimension.

What do cancer medical tourists care about? Content analysis based on network texts