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National identity has a profound impact on building a modern state, maintaining social stability and promoting economic development. Based on three waves of data collected from the World Values Survey (WVS) in Hong Kong between 2005 and 2018, this study aims to examine the changes in the national identity awareness of Hong Kongese over time.

The data used in this paper originate from the WVS. The WVS is a cross-country time-series survey that has been carried out in seven waves in 85 countries around the world, since 1981. There are three waves of data involving Hong Kong, which were obtained from the surveys in 2005, 2014 and 2018.

This study examined the changes in the national identity awareness of Hong Kongese over time and found that this has shown both continuity and rupture. Extreme groups lacking national identity have emerged and become more common over the decades and the elites’ national identity is much stronger than that of the lower and middle classes. It also shows that political trust, social capital, subjective well-being and possession of authoritarian personality have strong explanatory power for the changes in Hong Kongese national identity over time, but their explanatory strength varies across eras.

Based on three waves of surveys conducted by the WVS in Hong Kong in 2005, 2014 and 2018, respectively, this paper charts these changes over time and explores the differences in how they are influenced by political trust, social capital, subjective well-being and authoritarian personality.

The purpose is to provide decision support for tourists recommending scenic spots and corresponding suggestions for the management of scenic spots.

Based on the Baidu index data generated, this paper analyzes the temporal and spatial characteristics of network attention of 5A scenic spots in Sichuan Province. The online comment data are used to build the assessment model of scenic spots based on network attention, and the comment information of tourists is mined and analyzed through statistical analysis. At the same time, the key attributes of scenic spots from the perspective of network attention are evaluated and analyzed by using the probabilistic linguistic term set. Finally, this paper further constructs a recommendation model based on the key attribute set of scenic spots.

This paper uses different types of tourism network information, integrates multi-types of data and methods, fully excavates the value information of tourism network information, constructs the research framework of “scenic spot assessment + scenic spot recommendation” from the perspective of network attention, analyzes the network attention characteristics of scenic spots, evaluates the performance of scenic spots, and implements scenic spot recommendation.

This paper integrates multi-source data and multidisciplinary theoretical methods to form a scenic spot research framework of “assessment + recommendation” from the perspective of network attention.