网络舆情对旅游目的地网络关注度的时空影响——以“雪乡宰客”事件为例
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摘要
以冰雪旅游目的地雪乡为个案,运用Arc GIS的自然断裂法、回归分析法等,从时间维度与空间维度分析网络舆情对旅游目的地网络关注度的影响,以及旅游目的地网络关注度空间分异的影响因素。研究发现:"雪乡宰客"事件的网络舆情生命周期呈现双峰演化特征,依次经历酝酿期、爆发期、波动延续期、衰退期等4个阶段,网络关注度和媒体关注度具有协同演化的时变轨迹;"雪乡宰客"事件网络舆情呈现出从东往西梯度递减的空间分异特征,且雪乡网络关注度空间分异的影响因素差异显著。据此,建议实施契合舆情生命周期的应对策略和区域差异化的形象恢复策略,以期为旅游目的地舆情应对与风险治理提供一定的参考。
Taking Snow Township,an ice and snow tourism destination as an example,using Arc GIS natural fracture method and regression analysis method,the influence of network public opinion on the network attention to tourism destination from the temporal-spatial dimension and the influencing factors of spatial differentiation of network attention of tourism destination are analyzed.The study finds that the life cycle of network public opinion of " Snow Township Slaughter" presents a bimodal evolutionary characteristic,which goes through the following four stages: gestation period,explosion period,fluctuation continuation period and recession period.Network attention and media attention have a time-varying track of co-evolution.The network public opinion of " Snow Township Slaughter" event presents a spatial differentiation characteristic of decreasing gradient from east to west.There are significant differences in the influencing factors of spatial differentiation of attention.Based on this,it is proposed to implement a coping strategy that fits into the life cycle of network public opinion and image restoration strategies of regional differentiation in order to provide some reference for public opinion response and risk management of tourist destination.
Taking Snow Township,an ice and snow tourism destination as an example,using Arc GIS natural fracture method and regression analysis method,the influence of network public opinion on the network attention to tourism destination from the temporal-spatial dimension and the influencing factors of spatial differentiation of network attention of tourism destination are analyzed.The study finds that the life cycle of network public opinion of " Snow Township Slaughter" presents a bimodal evolutionary characteristic,which goes through the following four stages: gestation period,explosion period,fluctuation continuation period and recession period.Network attention and media attention have a time-varying track of co-evolution.The network public opinion of " Snow Township Slaughter" event presents a spatial differentiation characteristic of decreasing gradient from east to west.There are significant differences in the influencing factors of spatial differentiation of attention.Based on this,it is proposed to implement a coping strategy that fits into the life cycle of network public opinion and image restoration strategies of regional differentiation in order to provide some reference for public opinion response and risk management of tourist destination.
引文
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[3]RITTICHAINUWAT B.A travel barrier to tourism recovery[J].Annals of Tourism Research,2011,38(2):437-459.
[4]付业勤,郑向敏.网络新媒体时代旅游网络舆情研究:源起、价值与构想[J].河北学刊,2013,33(5):182-184.
[5]付业勤,曹娜.基于扎根理论量表开发的网络舆情对旅游地形象传播研究[J].统计与决策,2016(20):65-68.
[6]刘萌玥,陈效萱,吴建伟,等.旅游景区网络舆情指标体系构建---基于蚂蜂窝网全国百家5A级景区的游客评论[J].资源开发与市场,2017,33(1):80-84.
[7]付业勤,郑向敏,郑文标,等.旅游危机事件网络舆情的监测预警指标体系研究[J].情报杂志,2014,33(8):184-189.
[8]付业勤,陈雪钧.基于旅游消费者感知的旅游网络舆情危机研究[J].求索,2016(1):36-40.
[9]董坚峰,肖丽艳.旅游突发事件中的网络舆情预警研究[J].现代情报,2015,35(6):20-24.
[10]付业勤,陈雪钧,郑向敏,等.旅游危机事件网络舆情应对水平的评价研究:基于灰色统计和熵权TOPSIS方法[J].重庆师范大学学报(自然科学版),2015,32(2):162-167.
[11]王璟琦,李锐,吴华意.基于空间自相关的网络舆情话题演化时空规律分析[J].数据分析与知识发现,2018(2):64-73.
[12]杨海全.雪乡今冬旅游季接待游客629974人次创历史新高[EB/OL].(2017-02-20)[2018-11-10].http://hlj.people.com.cn/n2/2017/0220/c220024-29737256.html.
[13]马丽君,马曼曼.“天价虾”事件对青岛旅游网络关注度的影响[J].资源开发与市场,2018,34(1):83-87.
[14]陈海汉,陈婷.突发事件网络舆情传播时段特征和政府预警模式研究[J].图书馆学研究,2015(1):24-30.
[15]何琼峰.国内居民出游意愿的影响因素及区域格局[J].经济地理,2011,31(10):1754-1760.
[16]邹永广,林炜铃,郑向敏.旅游安全网络关注度时空特征及其影响因素[J].旅游学刊,2015,30(2):101-109.
[17]李霞,曲洪建.邮轮旅游网络关注度的时空特征和影响因素---基于百度指数的研究[J].统计与信息论坛,2016,31(4):101-106.