The COVID-19 pandemic has affected people's lives around the world on an unprecedented scale. We intend to investigate hoarding behaviors in response to the pandemic using large-scale social media data. First, we collect hoarding-related tweets shortly after the outbreak of the coronavirus. Next, we analyze the hoarding and anti-hoarding patterns of over 42,000 unique Twitter users in the United States from March 1 to April 30, 2020, and dissect the hoarding-related tweets by age, gender, and geographic location. We find the percentage of females in both hoarding and anti-hoarding groups is higher than that of the general Twitter user population. Furthermore, using topic modeling, we investigate the opinions expressed towards the hoarding behavior by categorizing these topics according to demographic and geographic groups. We also calculate the anxiety scores for the hoarding and anti-hoarding related tweets using a lexical approach. By comparing their anxiety scores with the baseline Twitter anxiety score, we reveal further insights. The LIWC anxiety mean for the hoarding-related tweets is significantly higher than the baseline Twitter anxiety mean. Interestingly, beer has the highest calculated anxiety score compared to other hoarded items mentioned in the tweets.
翻译:COVID-19大流行以前所未有的规模影响全世界人民的生活。 我们打算利用大规模社交媒体数据调查针对该流行病的囤积行为。 首先,我们在冠状病毒爆发后不久收集与囤积有关的推文。 其次,我们分析美国42 000多个独特推特用户从3月1日至4月30日、2020年3月1日至4月30日的囤积和反观光模式,并用年龄、性别和地理位置来比较与囤积有关的推文。我们发现,在囤积和反观光团体中,女性的比例都高于一般推特用户群体。此外,我们利用主题模型,根据人口和地理群体分类,调查对囤积行为表达的意见。 我们还用一种通俗称的方法计算囤积和反观光相关推文的推文的焦虑程度。我们通过比较其焦虑得分与基线Twitter焦虑得分,我们发现了进一步的认识。 与蓄积相关推文相关的推文的焦虑程度比,其他推算得最高。 有趣的是,啤酒比计算得最高分。