AI is used in social media to analyze user behavior, personalize content recommendations, and detect trends or sentiment. It employs machine learning algorithms and natural language processing to understand and categorize user-generated content, optimize ad targeting, and enhance user experiences on social media platforms.
"Lero's new public survey aims to uncover citizens' hopes and fears about AI and software, focusing on issues of responsibility and ethics. This project seeks to address the underrepresentation of public sentiment in ongoing debates, amidst rising concerns over biases in AI and potential human rights abuses."
Technology experts convened at Oak Ridge National Laboratory's Department of Energy for the Trillion-Pixel GeoAI Challenge workshop to discuss the future of geospatial systems. The event emphasized advancements in artificial intelligence, cloud infrastructure, high-performance computing, and remote sensing, highlighting their potential in addressing national and human security concerns like disaster response and land-use planning.
Researchers propose a visual analytics pipeline that leverages citizen volunteered geographic information (VGI) from social media to enhance impact-based weather warning systems. By combining text and image analysis, machine learning, and interactive visualization, they aim to detect and explore extreme weather events with greater accuracy and provide valuable localized information for disaster management and resilience planning.
Researchers introduce a speech emotion recognition (SER) system that accurately predicts a speaker's emotional state using audio signals. By employing convolutional neural networks (CNN) and Mel-frequency cepstral coefficients (MFCC) for feature extraction, the proposed system outperforms existing approaches, showcasing its potential in various applications such as human-computer interaction and emotion-aware technologies.
Large-scale multi-label dataset, Incidents1M, is introduced for incident detection and image-filtering experiments on social media. It enables timely understanding of natural disaster progression and aftermath using automated methods.
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