基于网络游记的新疆旅游流网络特征研究
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摘要
文章以新疆为研究区,利用网络游记获得国内游客在新疆各个旅游景点之间的流动信息,以此为基础构建新疆国内旅游流网络结构,并以社会网络的角度对其进行系统分析。研究结论表示:(1)新疆的旅游景区景点较多,但彼此之间有较强联系的只有42家景点,它们之间的旅游流网络密度仅为0.0598,说明景点之间的关系非常疏散;(2)从中心性角度看,乌鲁木齐市作为重要集散中心,具有非常高的中心度;此外,喀纳斯、赛里木湖、乌尔禾魔鬼城、那拉提草原、火焰山、伊犁及布尔津县等景点的中性度也比较高,已变成北疆旅游的中心;(3)从整体看,新疆国内旅游流网络由5个子群组成,其中自然风景线路子群的内部密度最高,其次为草原旅游线路,其余子群的内部密度普遍很低。
Internet travel is a tourist tour of the sense, to a large extent reflect the tourist behavior characteristics and intentions of tourism. This paper takes Xinjiang as the research area and uses the online travel to get the flow information of the domestic tourists in Xinjiang from various tourist attractions. Based on this, the paper constructs the domestic tourism flow network structure in Xinjiang, and makes a systematic analysis from the social network point of view. The conclusion of the study shows that:(1) There are only 42 tourist attractions in Xinjiang, but there are only 44 attractions between them. The network density between them is only 0.0598, which indicates that the relationship between the attractions is very evacuated.(2)From the central point of view, Urumqi City as an important distribution center, has a very high degree of center; In addition, Kanas, Nalati, Wuerhe devil city and Sailimu Lake and other attractions are more neutral.(3)From the whole, Xinjiang domestic tourism flow network consists of five sub-groups, of which the natural landscape sub-group has the highest density, followed by grassland tourist routes, the internal density of the remaining sub-groups is generally low.
Internet travel is a tourist tour of the sense, to a large extent reflect the tourist behavior characteristics and intentions of tourism. This paper takes Xinjiang as the research area and uses the online travel to get the flow information of the domestic tourists in Xinjiang from various tourist attractions. Based on this, the paper constructs the domestic tourism flow network structure in Xinjiang, and makes a systematic analysis from the social network point of view. The conclusion of the study shows that:(1) There are only 42 tourist attractions in Xinjiang, but there are only 44 attractions between them. The network density between them is only 0.0598, which indicates that the relationship between the attractions is very evacuated.(2)From the central point of view, Urumqi City as an important distribution center, has a very high degree of center; In addition, Kanas, Nalati, Wuerhe devil city and Sailimu Lake and other attractions are more neutral.(3)From the whole, Xinjiang domestic tourism flow network consists of five sub-groups, of which the natural landscape sub-group has the highest density, followed by grassland tourist routes, the internal density of the remaining sub-groups is generally low.
引文
[1]Fabien Girardin,Josep Blat,Francesco Calabrrese,et al,Digital Footprinting:Uncovering tourists with user-gen-erated content[J]. IEEE Pervasive Computing,2008,7(4):36-43.
[2]李君轶.旅游数字足迹:在线揭示游客的时空轨迹[J].思想战线,2013,39(3):103-107.
[3]张妍妍,李君轶,杨敏.基于旅游数字足迹的西安旅游流网络结构研究[J].人文地理,2014,29(04):111-118.
[4]梁保尔,潘植强.基于旅游数字足迹的目的地关注度与共现效应研究——以上海历史街区为例[J].旅游学刊,2015,30(07):80-90.
[5]李艳,严艳,贠欣.基于旅游数字足迹的西藏景区空间结构分析[J].干旱区资源与环境,2015,29(06):176-182.
[6]张维亚,陶卓民,秦立,李涛.基于网络游记的苏州园林旅游者数字足迹空间响应研究[J].资源开发与市场,2016,32(07):886-891.
[7]查晓莉,陆林.基于旅游数字足迹的访沪国内旅游者时空行为研究[J].旅游研究,2017,9(04):63-73.
[8]杨敏,李君轶,杨利.基于旅游数字足迹的城市入境游客时空行为研究——以成都市为例,2015,06.
[9]曲静,吴铭.基于旅游数字足迹的甘肃省旅游流网络结构研究[J].旅游论坛,2018,11(01):113-124.
[10]刘军.整体网分析讲义:UCINET软件实用指南[M].上海:格致出版社,2009.
[11]刘军.社会网络分析导论[M].北京:社会科学文献出版社,2004:114-177.
[12]刘法建,张捷,陈冬冬.中国入境旅游流网络结构特征及动因研究[J].地理学报,2010,65(08):1013-1024.
[13]张高军,李君轶,张柳.华山风景区旅游形象感知研究——基于游客网络日志的文本分析,2011.
[14]黄莎,陈金华,陈秋萍.基于网络信息嵌入性的旅游目的地形象传,2012.
[15]赵振斌,党娇.基于网络文本内容分析的太白山背包旅游行为研究,2011.
[16]党娇,赵振斌,赵丽.太白山旅游者行为研究从博客分析视角,2011.
[17]叶如瑾.基于Web2.0照片交互平台的国际游客眼中的上海旅游意象研究,2013.
[18]田晓霞,肖婷婷,张金凤,李翠林.喀什旅游产业集群社会网络结构分析[J].干旱区资源与环境,2013,27(07):197-202.
[19]田晓霞,肖婷婷,张金凤.吐鲁番市旅游产业集群社会网络结构分析[J].特区经济,2013(03):94-97.
[20]张俊丽,张红,刘妍.社会网络视角下山西省旅游线路优化整合分析[J].资源开发与市场,2016,32(01):120-124.
[21]刘冰,曾国军,彭青.社会网络视角下旅游线路研究——以新疆为例[J].旅游学刊,2013,28(11):101-109.
[22]戴光全,陈欣.旅游者摄影心理初探——基于旅游照片的内容分析[J].旅游学刊,2009,24(07):71-77.
[23]赵华.中国入境旅游流空间分布及其演变分析研究[D].陕西师范大学,2007.
[24]张妍妍,李君轶,杨敏.基于旅游数字足迹的西安旅游流网络结构研究,2014,08.
[25]李露苗.基于数字足迹的重庆旅游流网络体系研究,2016,04.
[26]李艳,严艳,贠欣.基于旅游数字足迹的西藏景区空间结构分析,2015,06.
[2]李君轶.旅游数字足迹:在线揭示游客的时空轨迹[J].思想战线,2013,39(3):103-107.
[3]张妍妍,李君轶,杨敏.基于旅游数字足迹的西安旅游流网络结构研究[J].人文地理,2014,29(04):111-118.
[4]梁保尔,潘植强.基于旅游数字足迹的目的地关注度与共现效应研究——以上海历史街区为例[J].旅游学刊,2015,30(07):80-90.
[5]李艳,严艳,贠欣.基于旅游数字足迹的西藏景区空间结构分析[J].干旱区资源与环境,2015,29(06):176-182.
[6]张维亚,陶卓民,秦立,李涛.基于网络游记的苏州园林旅游者数字足迹空间响应研究[J].资源开发与市场,2016,32(07):886-891.
[7]查晓莉,陆林.基于旅游数字足迹的访沪国内旅游者时空行为研究[J].旅游研究,2017,9(04):63-73.
[8]杨敏,李君轶,杨利.基于旅游数字足迹的城市入境游客时空行为研究——以成都市为例,2015,06.
[9]曲静,吴铭.基于旅游数字足迹的甘肃省旅游流网络结构研究[J].旅游论坛,2018,11(01):113-124.
[10]刘军.整体网分析讲义:UCINET软件实用指南[M].上海:格致出版社,2009.
[11]刘军.社会网络分析导论[M].北京:社会科学文献出版社,2004:114-177.
[12]刘法建,张捷,陈冬冬.中国入境旅游流网络结构特征及动因研究[J].地理学报,2010,65(08):1013-1024.
[13]张高军,李君轶,张柳.华山风景区旅游形象感知研究——基于游客网络日志的文本分析,2011.
[14]黄莎,陈金华,陈秋萍.基于网络信息嵌入性的旅游目的地形象传,2012.
[15]赵振斌,党娇.基于网络文本内容分析的太白山背包旅游行为研究,2011.
[16]党娇,赵振斌,赵丽.太白山旅游者行为研究从博客分析视角,2011.
[17]叶如瑾.基于Web2.0照片交互平台的国际游客眼中的上海旅游意象研究,2013.
[18]田晓霞,肖婷婷,张金凤,李翠林.喀什旅游产业集群社会网络结构分析[J].干旱区资源与环境,2013,27(07):197-202.
[19]田晓霞,肖婷婷,张金凤.吐鲁番市旅游产业集群社会网络结构分析[J].特区经济,2013(03):94-97.
[20]张俊丽,张红,刘妍.社会网络视角下山西省旅游线路优化整合分析[J].资源开发与市场,2016,32(01):120-124.
[21]刘冰,曾国军,彭青.社会网络视角下旅游线路研究——以新疆为例[J].旅游学刊,2013,28(11):101-109.
[22]戴光全,陈欣.旅游者摄影心理初探——基于旅游照片的内容分析[J].旅游学刊,2009,24(07):71-77.
[23]赵华.中国入境旅游流空间分布及其演变分析研究[D].陕西师范大学,2007.
[24]张妍妍,李君轶,杨敏.基于旅游数字足迹的西安旅游流网络结构研究,2014,08.
[25]李露苗.基于数字足迹的重庆旅游流网络体系研究,2016,04.
[26]李艳,严艳,贠欣.基于旅游数字足迹的西藏景区空间结构分析,2015,06.