实时gpu加速社交媒体情绪处理和可视化

Eugene Ch’ng, Ziyang Chen, S. See
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引用次数: 3

摘要

在一个决策都基于信息的时代,数据可视化是数据分析的一个重要方面。数据可视化的方法,特别是那些能够处理大规模文本数据集并将其实时可视化为结构化信息的方法,对于监测社交媒体的趋势非常有用。在本文中,我们介绍了我们的GPU加速项目,该项目使用CUDA来分发和并行处理文本数据和分析,以便实时或接近实时地将信息可视化,作为未来实时应用程序的基础系统,用于监控社交媒体趋势,适用于政治选举,社交媒体分析,以及计算社会科学中对时间至关重要的其他需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time GPU-accelerated social media sentiment processing and visualization
Data visualization is an important aspect of data analytics in an age where decisions are all based on information. Approaches in data visualization, particularly those that have the capability of processing large-scale textual datasets and visualize them as structured information in real-time can be useful for monitoring trends in social media. In this article, we present our GPU accelerated project, which uses CUDA to distribute and parallelize the processing and analysis of textual data in order to visualize information in real-time, or close to real-time as a foundational system for the future of real-time applications which monitors trends in social media, applicable to political elections, social media analytics, and other needs in computational social sciences which are time-critical.
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