基于網絡關注度的天氣與旅游相關性分析——以長沙為例
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湖南省氣象局2017年重點課題(XQKJ17A001)資助


Relevance Analysis of Weather and Tourism Based on Network Attention: A Case Study of Changsha
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    摘要:

    為掌握網民對天氣、旅游的關注程度,分析天氣與旅游的相互關系。本研究以長沙國家氣象站2012—2018年逐日氣象觀測數據及百度指數為網絡關注度,利用趨勢分析、線性擬合等,分析氣溫、降水、相對濕度、日照時數等因子與長沙天氣、長沙全域旅游、長沙鄉村旅游網絡關注度的相關性。結果表明:三者的網絡關注度主要以移動用戶為主,約占80%以上;長沙天氣的網絡關注度與最低氣溫、相對濕度、風速、日照時數、降水量顯著相關,以本地用戶關注為主,占比66.4%,其次為北京、廣州、深圳、成都;大幅降溫、連續暴雨過程、雷電預警等天氣上新聞頭條的機率大、次數多;長沙全域旅游的網絡關注度與平均氣溫、最高氣溫、最低氣溫、風速、相對濕度顯著相關;長沙鄉村旅游網絡關注度與氣溫、降水量顯著相關;長沙天氣、長沙全域旅游的網絡關注度呈上升趨勢,長沙鄉村旅游的網絡關注度呈下降趨勢。游客人數受平均氣溫、平均最高氣溫、平均最低氣溫、日照時數的影響明顯。

    Abstract:

    In order to grasp the netizens’ attention to weather and tourism, the relationship between weather and tourism is analyzed. Based on the daily meteorological observation data of Changsha National Meteorological Station from 2012 to 2018 and Baidu Indexes as network attention, this study analyzes the meteorological factors such as temperature, precipitation, relative humidity, sunshine hours and Changsha Weather Network attention, Changsha global tourism network attention and Changsha rural travel network attention by using trend analysis and linear fitting. The results show that mobile users are the main focus of network attention; Changsha Weather network attention is significantly correlated with the lowest temperature, relative humidity, wind speed, sunshine hours, and precipitation; the probability and frequency of news headlines in the weather of drastical cooling, continuous rainstorm process, lightning warning and so on are large; and the network attention of the whole Changsha tourism is significantly correlated with average temperature, maximum temperature, minimum temperature, wind speed and relative humidity; the network attention of rural tourism is significantly correlated with temperature and precipitation; the network attention of Changsha weather, the whole Changsha tourism is on the rise, but the network attention Changsha rural tourism is on the decline; Changsha Weather Network attention is on the decline; Changsha Weather Network attention is on the rise. Local users account for 66.4%, followed by Beijing, Guangzhou, Shenzhen and Chengdu. The number of tourists is obviously affected by average temperature, average maximum temperature, average minimum temperature and sunshine hours.

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周威,陳朝暉,李仁鵬,肖碩.基于網絡關注度的天氣與旅游相關性分析——以長沙為例[J].氣象科技,2020,48(4):607~614

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  • 收稿日期:2019-07-03
  • 定稿日期:2019-12-02
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  • 在線發布日期: 2020-08-21
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