Towards Understanding Crisis Events On Online Social Networks Through Pictures

Extensive research has been conducted to identify, analyze and measure popular topics and public sentiment on Online Social Networks (OSNs) through text, especially during crisis events. However, little work has been done to understand such events through pictures posted on these networks. Given the...

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Vydané v:2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) s. 439 - 446
Hlavní autori: Dewan, Prateek, Suri, Anshuman, Bharadhwaj, Varun, Mithal, Aditi, Kumaraguru, Ponnurangam
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: New York, NY, USA ACM 31.07.2017
Edícia:ACM Conferences
Predmet:
Human-centered computing
Human-centered computing > Collaborative and social computing
Human-centered computing > Collaborative and social computing > Collaborative and social computing systems and tools
Human-centered computing > Collaborative and social computing > Collaborative and social computing systems and tools > Social networking sites
Human-centered computing > Collaborative and social computing > Collaborative and social computing theory, concepts and paradigms
Human-centered computing > Collaborative and social computing > Collaborative and social computing theory, concepts and paradigms > Social media
Human-centered computing > Collaborative and social computing > Collaborative and social computing theory, concepts and paradigms > Social networks
Information systems
Information systems > Data management systems
Information systems > Data management systems > Database design and models
Information systems > Data management systems > Database design and models > Graph-based database models
Information systems > Information retrieval
Information systems > Information retrieval > Retrieval tasks and goals
Information systems > Information retrieval > Retrieval tasks and goals > Sentiment analysis
Information systems > Information retrieval > Specialized information retrieval
Information systems > World Wide Web
Information systems > World Wide Web > Web applications
Information systems > World Wide Web > Web applications > Social networks
Networks
Networks > Network types
Networks > Network types > Overlay and other logical network structures
Networks > Network types > Overlay and other logical network structures > Social media networks
ISBN:1450349935, 9781450349932
ISSN:2473-991X
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Popis
Shrnutí:Extensive research has been conducted to identify, analyze and measure popular topics and public sentiment on Online Social Networks (OSNs) through text, especially during crisis events. However, little work has been done to understand such events through pictures posted on these networks. Given the potential of visual content for influencing users' thoughts and emotions, we perform a large-scale analysis to study and compare popular themes and sentiment across images and textual content posted on Facebook during the terror attacks that took place in Paris in 2015. We propose a generalizable and highly automated 3-tier pipeline which utilizes state-of-the-art computer vision techniques to extract high-level human understandable image descriptors. We used these descriptors to associate themes and sentiment with images, and analyzed over 57,000 images related to the Paris Attacks. We discovered multiple visual themes which were popular in images, but were not identifiable through text. We also uncovered instances of misinformation and false flag (conspiracy) theories among popular image themes, which were not prominent in user-generated textual content. Further, our analysis revealed that while textual content posted after the attacks reflected negative sentiment, images inspired positive sentiment. These findings suggest that large-scale mining of images posted on OSNs during crisis, and other news-making events can significantly augment textual content to understand such events.
ISBN:1450349935
9781450349932
ISSN:2473-991X
DOI:10.1145/3110025.3110062