ZHANG Yunkai,HUA Wei,LIU Yurun,et al.Analysis on Temporal and Spatial Characteristics of Network Attention of Weather Forecast based on Baidu Index[J].Journal of Chengdu University of Information Technology,2022,37(05):601-607.[doi:10.16836/j.cnki.jcuit.2022.05.017]
基于百度指数的天气预报关注度时空特征研究
- Title:
- Analysis on Temporal and Spatial Characteristics of Network Attention of Weather Forecast based on Baidu Index
- 文章编号:
- 2096-1618(2022)05-0601-07
- Keywords:
- meteorology; meteorological data; Baidu index; weather forecast; network attention; temporal and spatial characteristics
- 分类号:
- P49
- 文献标志码:
- A
- 摘要:
- 目前关于网络关注度相关研究主要集中于经济社会领域，而对天气预报网络关注度的分析还较少涉及。为探究天气预报网络关注度的时空变化特征，利用百度搜索指数和经济社会统计数据，采用变异系数、基尼系数和相关分析等统计方法对中国天气预报网络关注度的时空特征及影响因素进行分析。结果表明，2011-2019年，中国天气预报网络关注度总体呈上升趋势，且关注度多在春季和秋末较高，而冬末和初秋较低; 天气预报网络关注度的周内变化不明显，但主要节假日期间则表现出假日前较高，假期中较低的趋势。天气预报网络关注度也存在明显的区域差异，总体上中、东部经济发达地区关注度较高，而西部地区较低; 与此同时，省际间和“东—中—西”三大区域间的差异同样明显，但基尼系数总体呈现下降趋势，而“东—中—西”三大区域内天气预报网络关注度也存在明显的区域差异，西部地区的内部差异远大于东、中部地区，而东部地区内部差异最小。天气预报网络关注度的空间差异与区域经济发展水平、居民收入水平高低和自然灾害等多种因素有关，尤其受不同省份生产总值和城镇居民人均可支配收入影响最为显著，此外也与自然灾害损失存在一定联系，但相关关系相对较弱。
- Abstract:
- Currently, the research on network attention is mainly focused on the economic and social field, while the analysis of weather forecast network attention is seldom involved. In order to explore the spatio-temporal variation characteristics of network attention of weather forecast, on the basis of Baidu search index and economic and social statistical data, the spatial and temporal characteristics of network attention of weather forecast and its influencing factors were analyzed by using the coefficient of variation, Gini coefficient and correlation analysis methods. The results show that the network attention of weather forecast shows an overall upward trend during 2011 to 2019, and is mostly high in spring and late autumn, while low in late winter and early autumn. The weekly variation of the network attention is not obvious and the network attention is high before the holidays and low during the holidays for the major holiday. There are also obvious regional differences in the network attention of weather forecast. Generally speaking, the network attention of weather forecast in central and eastern China is high, while it is low in western China. The differences among each province and the “east-central-west” regions are very obvious, but the Gini coefficient showed an overall downward trend, and the “east-central-west” regions also shows the obvious internal differences, and the internal differences is largest in western China, central China is second, and the eastern China is minimal. The spatial difference of network attention of weather forecast is caused by regional economic development level, residents’ income level and natural disasters. Furthermore, the network attention of weather forecast is mainly influenced by the GDP of different provinces and the per capita disposable income of urban residents. Moreover, although the network attention of weather forecast is also affected by natural disaster losses, but the impact is relatively small.
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备注/Memo
收稿日期:2022-09-01
基金项目:国家自然科学基金资助项目(41775072,42075019); 四川省杰出青年科技人才计划资助项目(2019JDJQ0001)