| There has long been a voice calling for the integration of tourism research and big data,but the empirical research is few.The current research chose typical tourism scenic spots as micro-scale research examples about tourism flow,started with the perspective of virtual network,used the platform of Sina Weibo,captured related big data on Weibo,and combined the methods of time stratification,empirical mode decomposition(EMD),kernel density to examine tourists' flow fluctuation characteristics in tourism areas and the space-time difference and evolvement rules different tourists have in scenic spots.This study emphasized the combination of theory and practice which applied the new data resources and methodologies to study micro-scale tourists flow.This article can be divided into five parts.The first part contains Chapter one and Chapter two,which points out the main scientific issue this article focus on and also gives out the background this scientific sits in and subsequent theoretical and practical significance.What is more,related concepts and supporting theories have been introduced and analyzed;detailed previous literature review has also been conducted.The second part(namely Chapter three)describes the acquisition and proceeding methods of Weibo sign data,including the invoking of application interfaces,the selection of acquisition time spans,the construction of coordinate center,the filtering of attributed data and the cleaning of noisy data etc.By using the longitudinal time layering method,the third part(Chapter four)applied EMD decomposition to compare the fluctuation characteristics of day-degree sign and week-degree sign tourists have in scenic spots.The fourth part(Chapter five)examine the space-time evolvement characteristics different sign points in scenic spots have by applying transverse time layering method while the last part(Chapter six)summarized the full text and point out what need to be improved in the near future.The research results are six-folded:(1)tourists' day-degree sign in Zhongshan Scenic Area shows a bimodal "M" distribution with male and female tourists,local and foreign tourists share the same distribution.The female tourists' sign is higher than the male's while local tourists' sign is more concentrated than foreign ones.Male and female tourists' sign characteristics have strong similarity and periodicity which shows significant characteristics of path to return;(2)the sign rule tourists have gave the priority to high-frequency oscillation,and made the low frequency oscillation as complementary which has no significant tendency and characteristics.The sign characteristics of male tourists and female tourists give priority to high-frequency week-degree oscillation and make low-frequency weekly oscillation as complementary.The male tourists are influenced greatly by holidays and season changes while female tourists are less likely to be influenced by external factors.Foreign tourists focus on weekly and monthly fluctuations with significant seasonal characteristics;(3)tourists under different time granularity reflect different sign rules which can help understand tourists' sign rules comprehensively and dialectically.In the condition of not covering high frequency cycle characteristics,improving data granularity will make it clearer to show middle and low frequency characteristics,but the high-granularity data behave actively in high-frequency period and cover characteristics in middle and low frequency periods;(4)two-day weekends are important periods for tourists' activities.Female tourists show more significant"holiday effect" than male tourists on weekends.Foreign tourists'sign characteristics do not show significant differences while the impact golden weeks have on local tourists are limited but local tourists are influenced by festivals in scenic spots greatly;(5)there is a "pyramid" structure of tourists,sign in scenic spots,which climbs the peak at noon.Festivals and climate are the main factors that influenced tourists'activities in scenic spots.In addition,female tourists'sign is high in tourist rush season which is contrast to the traditional thoughts that the female are easier to be restricted by society,meanwhile the female's emotional delicate characters make them prefer to share their emotion with others.Local tourists and foreign tourists show significant differences in activity characteristics in scenic spots with foreign tourists focus on the business time of scenic spots while the local tourists did not show significant rules;(6)tourists' sign characteristics in scenic spots is consistent with attraction distributions.The sign hot core area of Sun Yat-sen mausoleum scenic spot and soul valley temple scenic area,the sign hot core of the western mountain scenic area and the Ming tomb scenic area,and the second-level sign hot core area of Buddhist monk hill scenic spot area and southern leisure places form the spatial hot point distribution pattern in scenic spots.Four activity periods have been concluded in the space-time perspective,namely Scenic spot dormant,visit the initial period,peak scenic spots and tourist dispersed phase.And leisure places with dining and shopping functions have been detected as important parts of virtual spaces,in which tourists can spend their fragmental time and also reflects tourists' activities and rest conditions during different periods indirectly. |
PDF Full Text Request