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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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Dewan, Prateek Kumaraguru, Ponnurangam Suri, Anshuman Bharadhwaj, Varun Mithal, Aditi |
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| SubjectTerms | 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 |
| Title | Towards Understanding Crisis Events On Online Social Networks Through Pictures |
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