Exploring tourism networks in the Guangxi mountainous area using mobility data from user generated content

Tourism-led economic growth and tourism-driven urbanization have attracted increasing attention by provinces and regions in China with abundant tourism resources.Due to low data availability,the current tourism literature lacks empirical evidence of the tourism network in lessdeveloped mountainous regions where the development of transport infrastructure is more variable.This paper aims to provide such evidence using Guangxi Zhuang Autonomous Region in China as a case study.Using User Generated Content(UGC)data,this study constructs a tourism network in Guangxi.By integrating social network analysis with spatial interaction modelling,we compared the impact of two different transport infrastructures,highway and high-speed railway,on tourist flows,particularly in less-developed mountainous regions.It was found that the product of node centrality and flow could best describe the significant pushing and pulling forces on the flow of tourists.The tourism by high-speed railway was sensitive to the position of trip destination on the whole tourism network but self-drive tourism was more sensitive to travelling time.The increase of high-speed railway density is crucial to promote local tourism-led economic development,however,large-scale karst landforms in the study area present a significant obstacle to the construction of high-speed railways.

Relationship between scores and tags for Chinese books—In the case of Douban Book

Purpose:Currently,social tagging behavior,including social tag,online review and score information,has been investigated extensively,however,there are very few works about the relationship among them.In this paper,we have investigated the problem using Douban Website as the research object.Design/methodology/approach:Firstly,we divided social tags into those with high and low frequency counts,respectively,divided books into popular and unpopular books according to books’popularity,and chose core tags in terms of distribution;Secondly,we conducted an investigation on the relationship between social tags and books scores including comprehensive analyses and assorted analyses.Findings:The more popular the books become,the higher scores they will get.Tag frequency is not related with book scores directly,and neither does the tag distribution weight.Tags in books of'fashion'category are relatively disordered,which may associate with books miscellany and readers diversity.Research limitations:Social tags are growing dramatically,strategies and researches to this respect are just experimental exploration.Open source books,data and educational resources are not consummate.Comparative studies are necessary,but the result may be affected by researches based on data analyses.In addition,this research has been conducted only on one website,namely Douban,and the tags provided by Douban Book are not complete.All these factors could influence the versatility of the results.Practical implications:There are very a few studies that have been conducted on the relationship between tags and scores,and this research could bring a certain practical significance to popular books prediction and tags’quality research.Originality/value:Less attention has been paid to Chinese books while analyzing relationship between scores and tags of user generated content.Analyses based on the Chinese books may fill in the gap of better understanding the relationship between the two objects.