论文标题
NationalMood：通过网络搜索查询和移动传感器数据对人们情绪的大规模估计
NationalMood: Large-scale Estimation of People's Mood from Web Search Query and Mobile Sensor Data
论文作者
论文摘要
估计Web用户当前情感状态的能力具有巨大的潜力，可以实现以用户为中心的机会服务。但是，在现实世界中，确定用于此类估计的数据类型以及收集这种情感状况的基础真理。我们基于用户网络搜索查询和移动传感器数据的组合使用来提出一种新颖的估计方法。 Our large-scale data analysis with about 11,000,000 users and 100 recent advertisement log revealed (1) the existence of certain class of advertisement to which mood-status-based delivery would be significantly effective, (2) that our "National Mood Score" shows the ups and downs of people's moods in COVID-19 pandemic that inversely correlated to the number of patients, as well as the weekly mood rhythm of people.
The ability to estimate current affective statuses of web users has considerable potential towards the realization of user-centric opportune services. However, determining the type of data to be used for such estimation as well as collecting the ground truth of such affective statuses are difficult in the real world situation. We propose a novel way of such estimation based on a combinational use of user's web search queries and mobile sensor data. Our large-scale data analysis with about 11,000,000 users and 100 recent advertisement log revealed (1) the existence of certain class of advertisement to which mood-status-based delivery would be significantly effective, (2) that our "National Mood Score" shows the ups and downs of people's moods in COVID-19 pandemic that inversely correlated to the number of patients, as well as the weekly mood rhythm of people.
