Analysis of the emotional characteristics of people in earthquake-stricken areas based on social media data mining

Yanbo Cao; Yuanshuo Zhang

doi:10.1117/12.2667744

10 February 2023 Analysis of the emotional characteristics of people in earthquake-stricken areas based on social media data mining

Yanbo Cao, Yuanshuo Zhang

Author Affiliations +

Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 125521Q (2023) https://doi.org/10.1117/12.2667744
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China

Abstract

"Social perception technology" is a useful tool for analyzing the geographical and temporal aspects of people's behavioral responses during earthquakes. Using the magnitude 7.0 earthquake in Jiuzhaigou, Sichuan, China on August 9, 2017 as an example, this paper uses the method of combining emotion dictionary and rules to mine the social media data released by the disaster area 24 hours after the earthquake and analyze the earthquake microblog data, emotional polarity, and spatiotemporal characteristics. The number of active microblogs in this earthquake is highly related to population density, lifeline damage degree, epicenter distance and intensity, and the spatial distribution is imbalanced, according to the findings. The positive attitude in the disaster area outnumbers the bad mood. Population density, housing seismic performance, local people's understanding of earthquake avoidance and catastrophe mitigation, and popularization of earthquake scientific information are all key factors.

Citation Download Citation

Yanbo Cao and Yuanshuo Zhang "Analysis of the emotional characteristics of people in earthquake-stricken areas based on social media data mining", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 125521Q (10 February 2023); https://doi.org/10.1117/12.2667744

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