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.
CITATION STYLE
Hassan, S. Z., Ahmad, K., Al-Fuqaha, A., & Conci, N. (2019). Sentiment analysis from images of natural disasters. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11752 LNCS, pp. 104–113). Springer Verlag. https://doi.org/10.1007/978-3-030-30645-8_10
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