  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.
