Sentiment Analysis from Images of Natural Disasters
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Abstract (arXiv)
Social media have been widely exploited to detect and gather relevant information about opinions and events. However, the relevance of the information is very subjective and rather depends on the application and the end-users. In this article, we tackle a specific facet of social media data processing, namely the sentiment analysis of disaster-related images by considering people's opinions, attitudes, feelings and emotions. We analyze how visual sentiment analysis can improve the results for the end-users/beneficiaries in terms of mining information from social media. We also identify the challenges and related applications, which could help defining a benchmark for future research efforts in visual sentiment analysis.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Oct 2019.
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Citing papers per year: 2021: 7; 2022: 0; 2023: 0; 2024: 2; 2025: 1.
10 papers.
- 2021Affective Image Content Analysis: Two Decades Review and New Perspectivescited by 47
- 2021MEDIC: A Multi-Task Learning Dataset for Disaster Image Classificationcited by 20
- 2021Robust Training of Social Media Image Classification Models for Rapid Disaster Responsecited by 4
- 2021Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directionscited by 4
- 2024A Named Entity Recognition and Topic Modeling-based Solution for Locating and Better Assessment of Natural Disasters in Social Mediacited by 4
- 2021The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directionscited by 3
- 2021Visual Sentiment Analysis: A Natural DisasterUse-case Task at MediaEval 2021cited by 1
- 2021Deep Models for Visual Sentiment Analysis of Disaster-related Multimedia Contentcited by 0
- 2024Social Media Informatics for Sustainable Cities and Societies: An Overview of the Applications, associated Challenges, and Potential Solutionscited by 0
- 2025Social Media Data Mining of Human Behaviour during Bushfire Evacuationcited by 0
- 2025Social Media Data Mining of Human Behaviour during Bushfire Evacuation1 Dec 2025
- 2024Social Media Informatics for Sustainable Cities and Societies: An Overview of the Applications, associated Challenges, and Potential Solutions3 Dec 2024
- 2024A Named Entity Recognition and Topic Modeling-based Solution for Locating and Better Assessment of Natural Disasters in Social Media1 May 2024
- 2021Deep Models for Visual Sentiment Analysis of Disaster-related Multimedia Content30 Nov 2021
- 2021Visual Sentiment Analysis: A Natural DisasterUse-case Task at MediaEval 202122 Nov 2021
- 2021Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions26 Oct 2021
- 2021MEDIC: A Multi-Task Learning Dataset for Disaster Image Classification29 Aug 2021
- 2021Affective Image Content Analysis: Two Decades Review and New Perspectives30 Jun 2021
- 2021Robust Training of Social Media Image Classification Models for Rapid Disaster Response9 Apr 2021
- 2021The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions6 Apr 2021