運用文字探勘從網路新聞探討台灣COVID-19疫情期間民生物資與確診人數發展關係

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吳岱蓉(TAI-JUNG WU) 查詢紙本館藏

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企業管理學系在職專班

論文名稱

運用文字探勘從網路新聞探討台灣COVID-19疫情期間民生物資與確診人數發展關係
(Exploring the Relationship between the Development of Daily Necessities and Confirmed Cases during the COVID-19 Epidemic in Taiwan from Online News Based on Text Mining)

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至系統瀏覽論文 (2026-1-13以後開放)

摘要(中)

自2019年底起，新冠肺炎病毒COVID-19疫情開始爆發，在全世界範圍各方面都受到了巨大的影響與改變。在疫情期間，每當爆發大規模感染時，消費者都會產生恐慌性或預防性的大量消費和囤貨行為。因此本論文透過文字探勘方法，分析台灣疫情期間的新聞關鍵字，與使用Google Trends分析關鍵字熱度趨勢變化與確診人數之間的相關分析，並使用互相關分析不同物資關鍵字的熱度與確診人數間的延遲關係。透過延遲處理後，能發現民生物資與防疫物資在疫情不同發展階與確診人數間會有不同程度的延遲現象。與疫情相關新聞中的關鍵字和Google Trends上的關鍵字熱度趨勢有高度相關且同步的現象。本論文透過結合文字探勘方法與Google Trends關鍵字熱門度趨勢工具，能夠有效且快速的偵測到疫情期間不同物資需求的變化。

摘要(英)

Since the outbreak of COVID-19 at the end of 2019, the world has been greatly affected and changed in all aspects. During the epidemic, whenever a large-scale infection breaks out, consumers will have panic or precautionary large-scale consumption and hoarding behaviors. Therefore, this paper uses text mining methods to analyze news keywords during the epidemic in Taiwan, and uses Google Trends to analyze the correlation between keywords popularity trends and the number of confirmed cases, and uses cross-correlation to analyze the delay between the trends of different keywords of daily necessities and the number of confirmed cases. After delayed processing, it can be found that there will be varying degrees of delays between the development stages of the epidemic and the number of confirmed cases between the people′s daily necessities and epidemic prevention supplies. The keywords in news related to the epidemic are highly correlated and synchronized with the keyword popularity trend on Google Trends. In this paper, by combining the text mining method and the Google Trends tool, it can effectively and quickly detect changes in the demand for different necessities and supplies during the epidemic.

關鍵字(中)

★ COVID-19
★ 文字探勘
★ Google Trends
★ 民生物資
★ 延遲分析

關鍵字(英)

★ COVID-19
★ text mining
★ Google Trends
★ daily necessities
★ delay analysis

論文目次

目錄
圖目錄 vi
表目錄 vii
第一章緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
第二章文獻探討 3
2.1 台灣COVID-19疫情 3
2.2 文字探勘 4
2.3 Google Trends搜尋趨勢 6
第三章研究方法 10
3.1 資料蒐集與清理 11
3.2 資料分析 13
第四章研究分析與結果 14
4.1 高頻率疫情物資 14
4.2 新聞疫情物資詞頻與確診人數相關分析 15
4.3 Google Trends疫情物資熱門度與確診人數相關分析 21
4.4 新聞疫情物資詞頻與Google Trends疫情物資熱門度相關分析 25
第五章研究結論與建議 30
參考文獻 32

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指導教授

許秉瑜(Ping-Yu Hsu)

審核日期

2023-1-12

推文