Details of Research Outputs

TitleReal-time GPU-accelerated social media sentiment processing and visualization
Creator
Date Issued2017-12-05
Conference Name21st IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT)
Source PublicationProceedings - 2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2017
Volume2017-January
Pages1-4
Conference DateOCT 18-20, 2017
Conference PlaceRome, ITALY
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.

KeywordBig data GPU acceleration Real-time visualization Sentiment analysis Social media Twitter
DOI10.1109/DISTRA.2017.8167690
URLView source
Indexed ByCPCI-S
Language英语English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS IDWOS:000426923700031
Scopus ID2-s2.0-85042937065
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/10987
CollectionResearch outside affiliated institution
Corresponding AuthorCh'ng, Eugene
Affiliation
1.NVIDIA Joint-Lab on Mixed Reality,University of Nottingham,Ningbom,China
2.NVIDIA Technology APJ Centre,Singapore,Singapore
Recommended Citation
GB/T 7714
Ch'ng, Eugene,Chen, Ziyang,See, Simon. Real-time GPU-accelerated social media sentiment processing and visualization[C], 2017: 1-4.
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