@inproceedings{bee4ff5f917a45899c518b1a37bb544d,
title = "Sentiment analysis from images of natural disasters",
abstract = "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{\textquoteright}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.",
keywords = "CNNs, Multi-label classification, Natural disasters, Sentiment analysis, Social media",
author = "Hassan, \{Syed Zohaib\} and Kashif Ahmad and Ala Al-Fuqaha and Nicola Conci",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 20th International Conference on Image Analysis and Processing, ICIAP 2019 ; Conference date: 09-09-2019 Through 13-09-2019",
year = "2019",
doi = "10.1007/978-3-030-30645-8\_10",
language = "English",
isbn = "9783030306441",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "104--113",
editor = "Elisa Ricci and Nicu Sebe and \{Rota Bul{\`o}\}, Samuel and Cees Snoek and Oswald Lanz and Stefano Messelodi",
booktitle = "Image Analysis and Processing – ICIAP 2019 - 20th International Conference, Proceedings",
address = "Germany",
}