Wang Weichen, Wu Jialing, Nepal Subigya, daSilva Alex, Hedlund Elin, Murphy Eilis, Rogers Courtney, Huckins Jeremy
Dartmouth College, Hanover, NH, USA.
Proc ACM Int Conf Multimodal Interact. 2021 Oct;2021:425-434. doi: 10.1145/3462244.3479888. Epub 2021 Oct 18.
Pandemics significantly impact human daily life. People throughout the world adhere to safety protocols (e.g., social distancing and self-quarantining). As a result, they willingly keep distance from workplace, friends and even family. In such circumstances, in-person social interactions may be substituted with virtual ones via online channels, such as, Instagram and Snapchat. To get insights into this phenomenon, we study a group of undergraduate students before and after the start of COVID-19 pandemic. Specifically, we track N=102 undergraduate students on a small college campus prior to the pandemic using mobile sensing from phones and assign semantic labels to each location they visit on campus where they study, socialize and live. By leveraging their colocation network at these various semantically labeled places on campus, we find that colocations at certain places that possibly proxy higher in-person social interactions (e.g., dormitories, gyms and Greek houses) show significant predictive capability in identifying the individuals' change in social media usage during the pandemic period. We show that we can predict student's change in social media usage during COVID-19 with an F1 score of 0.73 purely from the in-person colocation data generated prior to the pandemic.
大流行对人类日常生活产生重大影响。全世界的人们都遵守安全协议（如社交距离和自我隔离）。因此，他们自愿与工作场所、朋友甚至家人保持距离。在这种情况下，面对面的社交互动可能会通过在线渠道（如照片墙和色拉布）被虚拟互动所取代。为了深入了解这一现象，我们对一组本科生在新冠疫情大流行开始前后进行了研究。具体而言，在疫情大流行之前，我们利用手机的移动传感技术对一个小学院校园里的N = 102名本科生进行跟踪，并为他们在校园里学习、社交和生活时所访问的每个地点赋予语义标签。通过利用他们在校园里这些语义标注的不同地点的共置网络，我们发现，在某些可能代表更高面对面社交互动的地点（如宿舍、健身房和兄弟会会所）的共置情况，在识别大流行期间个人社交媒体使用的变化方面具有显著的预测能力。我们表明，仅从疫情大流行之前生成的面对面共置数据，我们就能以0.73的F1分数预测学生在新冠疫情期间社交媒体使用的变化。
