论文标题
使用大规模的社交媒体数据了解Covid-19期间大流行期间的ho积行为
Understanding the Hoarding Behaviors during the COVID-19 Pandemic using Large Scale Social Media Data
论文作者
论文摘要
199年，共同的大流行已经以前所未有的规模影响了世界各地的人们的生活。我们打算使用大规模的社交媒体数据来调查大流行的ho积行为。首先，我们在冠状病毒爆发后不久收集与ho积有关的推文。接下来，我们分析了3月1日至2020年4月30日，在美国，超过42,000个独特的Twitter用户的ho积和反固定模式，并根据年龄，性别和地理位置剖析了与ho积有关的推文。我们发现，在ho积和反阻滞群体中，女性的百分比高于一般Twitter用户群体的百分比。此外，使用主题建模，我们通过根据人口统计和地理群体对这些主题进行分类来研究对ho积行为表达的观点。我们还使用词汇方法计算了ho积和反固定的推文的焦虑评分。通过将他们的焦虑分数与基线Twitter焦虑评分进行比较，我们揭示了进一步的见解。与ho积相关的推文的LIWC焦虑平均值明显高于基线Twitter焦虑症的平均值。有趣的是，与推文中提到的其他ho积项目相比，啤酒的焦虑得分最高。
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.
