|
|
Camelia Bellepeau, Hugo Bergere, Corentin Thevenet, Frédérick Bénaben, Nafe Moradkhani, & Thibaut Cerabona. (2022). Use of Physics of Decision to Assess how COVID-19 Impacted Air Pollution. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 887–894). Tarbes, France.
Abstract: This article focuses on the question of the impact of the COVID-19 crisis on air pollution. The chosen approach is based on the principle of “Physics of Decision” (POD), which considers: (i) the performance of a system as a physical trajectory within the framework of its performance indicators, (ii) risks or opportunities (potentialities) as forces that may deviate that trajectory, and (iii) benefits or damages (actualities) as concrete deviations of the performance trajectory. The daily data about the air pollution in Paris area (France) has been gathered for eight years (2014-2021) and three main performance indicators have been chosen. Then, the performance trajectory of each year has been plotted and the expected trajectories of 2020 and 2021 have been guessed from the previous ones. The deviation between the expected and actual trajectories of 2020 and 2021 have been assessed, and using physics and motion laws, evaluated as a deviation force.
|
|
|
|
Yongzhong Sha, Jinsong Yan, & Guoray Cai. (2014). Detecting public sentiment over PM2.5 pollution hazards through analysis of Chinese microblog. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 722–726). University Park, PA: The Pennsylvania State University.
Abstract: Decision-making in crisis management can benefit from routine monitoring of the (social) media to discover the mass opinion on highly sensitive crisis events. We present an experiment that analyzes Chinese microblog data (extracted from Weibo.cn) to measure sentiment strength and its change in relation to the recent PM 2.5 air pollution events. The data were analyzed using SentiStrength algorithm together with a special sentiment words dictionary tailored and refined for Chinese language. The results of time series analysis on detected sentiment strength showed that less than one percent of the posts are strong-positive or strong negative. Weekly sentiment strength measures show symmetric changes in positive and negative strength, but overall trend moved towards more positive opinions. Special attention was given to sharp bursts of sentiment strength that coincide temporally with the occurrence of extreme social events. These findings suggest that sentiment strength analysis may generate useful alert and awareness of pending extreme social events.
|
|
|
|
Yiwei Li, Yu Guo, & Naoya Ito. (2015). The Role of Information Quality and Efficacy Beliefs in Predicting Chinese People?s Information Seeking about Air Pollution Risk. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Information seeking is suggested as an important precursor of self-protective behavior. Therefore, ways of enhancing information seeking are expected to help individuals? precautionary action under conditions of risk. Builds upon previous efforts, a social-cognitive model of risk information seeking is constructed, presenting a new approach to meet the aforementioned expectation. Data were collected from a sample of Mainland Chinese people (N=1032). Results of path analysis demonstrated satisfactory model fit. Explanations on how the cognitive process resulted in information seeking may create a better understanding of individual behavior. Findings provide practical implications for communicating risks and for helping the public to make better decisions.
|
|
