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Open AccessArticle
An Aspect-Based Emotion Analysis Approach on Wildfire-Related Geo-Social Media Data — A Case Study of the 2020 California Wildfires
by
Christina Zorenböhmer
Christina Zorenböhmer
Shaily Gandhi
Shaily Gandhi
Sebastian Schmidt
Sebastian Schmidt 
and
Bernd Resch
Bernd Resch
1
Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria
2
Geosocial Artificial Intelligence, Interdisciplinary Transformation University Austria, 4040 Linz, Austria
3
Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2025, 14(8), 301; https://doi.org/10.3390/ijgi14080301 (registering DOI)
Submission received: 4 April 2025
/
Revised: 15 July 2025
/
Accepted: 27 July 2025
/
Published: 1 August 2025
Abstract
Natural disasters like wildfires pose significant threats to communities, which necessitates timely and effective disaster response strategies. While Aspect-based Sentiment Analysis (ABSA) has been widely used to extract sentiment-related information at the sub-sentence level, the corresponding field of Aspect-based Emotion Analysis (ABEA) remains underexplored due to dataset limitations and the increased complexity of emotion classification. In this study, we used EmoGRACE, a fine-tuned BERT-based model for ABEA, which we applied to georeferenced tweets of the 2020 California wildfires. The results for this case study reveal distinct spatio-temporal emotion patterns for wildfire-related aspect terms, with fear and sadness increasing near wildfire perimeters. This study demonstrates the feasibility of tracking emotion dynamics across disaster-affected regions and highlights the potential of ABEA in real-time disaster monitoring. The results suggest that ABEA can provide a nuanced understanding of public sentiment during crises for policymakers.
Share and Cite
MDPI and ACS Style
Zorenböhmer, C.; Gandhi, S.; Schmidt, S.; Resch, B.
An Aspect-Based Emotion Analysis Approach on Wildfire-Related Geo-Social Media Data — A Case Study of the 2020 California Wildfires. ISPRS Int. J. Geo-Inf. 2025, 14, 301.
https://doi.org/10.3390/ijgi14080301
AMA Style
Zorenböhmer C, Gandhi S, Schmidt S, Resch B.
An Aspect-Based Emotion Analysis Approach on Wildfire-Related Geo-Social Media Data — A Case Study of the 2020 California Wildfires. ISPRS International Journal of Geo-Information. 2025; 14(8):301.
https://doi.org/10.3390/ijgi14080301
Chicago/Turabian Style
Zorenböhmer, Christina, Shaily Gandhi, Sebastian Schmidt, and Bernd Resch.
2025. "An Aspect-Based Emotion Analysis Approach on Wildfire-Related Geo-Social Media Data — A Case Study of the 2020 California Wildfires" ISPRS International Journal of Geo-Information 14, no. 8: 301.
https://doi.org/10.3390/ijgi14080301
APA Style
Zorenböhmer, C., Gandhi, S., Schmidt, S., & Resch, B.
(2025). An Aspect-Based Emotion Analysis Approach on Wildfire-Related Geo-Social Media Data — A Case Study of the 2020 California Wildfires. ISPRS International Journal of Geo-Information, 14(8), 301.
https://doi.org/10.3390/ijgi14080301
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