Impact of COVID-19 on online grocery shopping discussion and behavior reflected from Google Trends and geotagged tweets.

IF 2.6 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computational urban science Pub Date : 2023-01-01 DOI:10.1007/s43762-023-00083-0
Nemin Wu, Lan Mu
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Abstract

People express opinions, make connections, and disseminate information on social media platforms. We considered grocery-related tweets as a proxy for grocery shopping behaviors or intentions. We collected data from January 2019 to January 2022, representing three typical times of the normal period before the COVID-19 pandemic, the outbreak period, and the widespread period. We obtained grocery-related geotagged tweets using a search term index based on the top 10 grocery chains in the US and compiled Google Trends online grocery shopping data. We performed a topic modeling analysis using the Latent Dirichlet Allocation (LDA), and verified that most of the collected tweets were related to grocery-shopping demands or experiences. Temporal and geographical analyses were applied to investigate when and where people talked more about groceries, and how COVID-19 affected them. The results show that the pandemic has been gradually changing people's daily shopping concerns and behaviors, which have become more spread throughout the week since the pandemic began. Under the causal impact of COVID-19, people first experienced panic buying groceries followed by pandemic fatigue a year later. The normalized tweet counts show a decrease of 40% since the pandemic began, and the negative causal effect can be considered statistically significant (p-value = 0.001). The variation in the quantity of grocery-related tweets also reflects geographic diversity in grocery concerns. We found that people in non-farm areas with less population and relatively lower levels of educational attainment tend to act more sensitively to the evolution of the pandemic. Utilizing the COVID-19 death cases and consumer price index (CPI) for food at home as background information, we proposed an understanding of the pandemic's impact on online grocery shopping by assembling, geovisualizing, and analyzing the evolution of online grocery behaviors and discussion on social media before and during the pandemic.

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2019冠状病毒病对谷歌趋势和地理标记推文反映的在线杂货购物讨论和行为的影响。
人们在社交媒体平台上表达意见、建立联系、传播信息。我们认为与杂货店相关的推文是杂货店购物行为或意图的代理。我们收集了2019年1月至2022年1月的数据,代表了COVID-19大流行前的正常时期、爆发期和广泛传播期的三个典型时期。我们使用基于美国十大连锁杂货店的搜索词索引获得了与杂货店相关的地理标记推文,并编译了谷歌趋势在线杂货店购物数据。我们使用潜狄利克雷分配(Latent Dirichlet Allocation, LDA)进行了主题建模分析,并验证了大多数收集到的推文都与杂货店购物需求或体验相关。时间和地理分析应用于调查人们在何时何地更多地谈论杂货,以及COVID-19如何影响他们。结果显示,疫情正在逐渐改变人们的日常购物关注和行为,自疫情开始以来的一周内,这种关注和行为变得更加普遍。在COVID-19的因果影响下,人们首先经历了恐慌性购买杂货,一年后出现了大流行疲劳。标准化的推文计数显示,自大流行开始以来减少了40%,负因果效应可以被认为具有统计学意义(p值= 0.001)。与食品杂货相关的推文数量的变化也反映了食品杂货关注的地理多样性。我们发现,在人口较少、受教育程度相对较低的非农业地区,人们往往对大流行的演变更为敏感。我们利用COVID-19死亡病例和家庭食品消费者价格指数(CPI)作为背景信息,通过汇总、地理可视化和分析在线杂货行为的演变以及大流行之前和期间社交媒体上的讨论,提出了对大流行对在线杂货购物的影响的理解。
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