Generating Metrics for High-Performance Computing Clusters

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Partner: Unity DS4CG 2023. Unity is a collaborative, multi-institutional high-performance computing cluster, primarily used for research computing. The Unity project focused on generating useful metrics and analysis for Unity by building a pipeline to a database that could power a live dashboard for Unity’s admin staff. Metrics included unnecessarily idle GPUs, daily and weekly node usage, total resource usage, and wait time. Additionally, a prediction model for wait time at job submission time was built.

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Detecting Extreme Speech in YouTube Videos

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Partner: Media Cloud The surge in multimodal content shared online, particularly on platforms like YouTube and Instagram, has increased the need for effective extreme and hateful speech detection systems. Current systems often fail to address the nuanced challenges of detecting explicit and implicit hate speech in multimodal contexts, where speech and text combine to convey harmful messages. Media Cloud, an open-source media research platform, helps researchers study news and information flow globally. This DS4CG team worked in collaboration with Media Cloud to focus on advancing multimodal hate speech detection by addressing three key challenges: the lack of comprehensive, human-annotated datasets; the absence of systems capable of analyzing both audio and text data simultaneously; and the need for fine-grained detection of subtle hate speech. The study leverages distinct latent features from audio and text to improve…

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Extracting Bylines from Media in Multiple Languages

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Partner: Media Cloud Over the past few decades, the rapid expansion of digital media has transformed how information is shared and consumed. However, this growth presents challenges such as content moderation, misinformation detection, and addressing media bias. Categorizing articles by authors or agencies has become a critical step in tackling these issues, especially for both high- and low-resource settings. This DS4CG project evaluated existing and newly implemented tools for extracting author names from news articles. Using Media Cloud’s article archive, 100 documents from 10 languages were sampled and annotated by volunteers fluent in each language, following guidelines developed with the Media Cloud team. A pipeline was designed to test these tools, and their performance was assessed using five NLP metrics.

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Analyzing Energy Usage with Predictive Modeling

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Partner: Massachusetts Division of Capital Asset Management & Maintenance DS4CG 2023. DCAMM is responsible for managing resources in various state buildings like state hospitals, prisons, universities, community colleges, office buildings. This project analyzed 5 year energy usage of 279 utility meters in 23 academic buildings. Using this data, time-series prediction models were developed for 12-month energy consumption of various utilities (electricity, steam, natural gas, water) by building. Prediction is the first step towards data-driven efficient management of energy resources and energy conservation.

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