Abstract
PM2.5 not only harms physical health but also has negative impacts on the public’s wellbeing and cognitive and behavioral patterns. However, traditional air quality assessments may fail to provide comprehensive, real-time monitoring of air quality because of the sparse distribution of air quality monitoring stations. Overcoming some key limitations of traditional surface monitoring data, Web-based social media platforms, such as Twitter, Weibo, and Facebook, provide a promising tool and novel perspective for environmental monitoring, prediction, and evaluation. This study aims to investigate the relationship between PM2.5 levels and people’s emotional intensity by observing social media postings. This study defines the “emotional intensity” indicator, which is measured by the number of negative posts on Weibo, based on Weibo data related to haze from 2016 and 2017. This study estimates sentiment polarity using a recurrent neural networks model based on LSTM (Long Short-Term Memory) and verifies the correlation between high PM2.5 levels and negative posts on Weibo using a Pearson correlation coefficient and multiple linear regression model. This study makes the following observations: (1) Taking the two-year data as an example, this study recorded the significant influence of PM2.5 levels on netizens’ posting behavior. (2) Air quality, meteorological factors, the seasons, and other factors have a strong influence on netizens’ emotional intensity. (3) From a quantitative viewpoint, the level of PM2.5 varies by 1 unit, and the number of negative Weibo posts fluctuates by 1.0168 units. Thus, it can be concluded that netizens’ emotional intensity is significantly positively affected by levels of PM2.5. The high correlation between PM2.5 levels and emotional intensity and the sensitivity of social media data shows that social media data can be used to provide a new perspective on the assessment of air quality.
Highlights
IntroductionIndustrial pollution, automobile exhaust, the use of coal-fired heating, and other problems are resulting in a growing number of haze episodes [1]
With the advancement of industrialization in Chinese cities and the trend towards increasing urbanization in China, environmental issues are becoming increasingly pressing.Industrial pollution, automobile exhaust, the use of coal-fired heating, and other problems are resulting in a growing number of haze episodes [1]
This study observed an interesting phenomenon: the numbers of positive and negative Weibo posts are positively correlated with PM2.5 levels
Summary
Industrial pollution, automobile exhaust, the use of coal-fired heating, and other problems are resulting in a growing number of haze episodes [1]. State of China’s Ecological Environment in 2017, the days of heavy pollution in 338 cities of China account for 1.9% of the year; the days of severe pollution account for 0.6% of the year. The days with PM2.5 as the primary pollutant accounted for 74% of days with heavy or relatively severe pollution, days with PM10 as the primary pollutant accounted for 20%, and days with O3 as the primary pollutant accounted for 6%, PM2.5 is the main component of haze. Many studies have shown that severe haze affects physical and mental health, and deals a heavy blow to society in many other ways. The increase in air humidity and pollution during haze episodes can cause damage to power
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