Research topic: Tourists' preference for public space based on Big Data online. Case study: Fuzhou National Forest Park

Abstract

Taking the Fuzhou National Forest Park as the research sample, this study uses the crawler tool to capture the comments of tourists on the network of Fuzhou National Forest Park, and uses ROST6.0 information mining software to analyze the emotional distribution and classification of word frequency. When analysed, the results showed that: (1) On the whole, tourists showed positive emotions towards Fuzhou National Forest Park, and the proportion of their neutral emotions and negative emotions was small. (2) Visitors' favourite activities were "barbecuing", "mountain hiking", "leisure", "walking", "sightseeing", "playing games", "exercising", "tourist-visit", "entertainment" and "picnicking". (3) Visitors' favourite scenic spots in turn were "Banyan", "Sakura blossoms", "Peach Blossom", "Bird Language Forest", "Longtan pond", "trees", "Botanical Garden", "waterfall", "vegetation", "reservoir", "garden", "museum", "Bamboo forest" and "Plank road" (4) In the insufficiency aspect, the Fuzhou National Forest Park had the situation where there are too many people queuing up at certain times of the day. Finally, a set of public space management mechanism based on Big Data is summarized, which provides theoretical support for its management and optimization.