@inproceedings{c36a4d06400e469982e0094f12f2b7bf,
title = "Real-time GPU-accelerated social media sentiment processing and visualization",
abstract = "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.",
keywords = "Big data, GPU acceleration, Real-time visualization, Sentiment analysis, Social media, Twitter",
author = "Eugene Ch'ng and Ziyang Chen and Simon See",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 21st IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2017 ; Conference date: 18-10-2017 Through 20-10-2017",
year = "2017",
month = dec,
day = "5",
doi = "10.1109/DISTRA.2017.8167690",
language = "English",
series = "Proceedings - 2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--4",
editor = "Alfredo Garro and Andrea D'Ambrogio and {De Grande}, Robson and Andrea Tundis",
booktitle = "Proceedings - 2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2017",
address = "United States",
}