Sentiment Analysis Using Parallel Computing Through GPU

Authors(2) :-Harshita Mandloi, Shraddha Masih

Parallel Computing is becoming important in the field of computer science and is proven as a high-performance solution. Over the couple of years, GPU has gained an important place in the field of high-performance computing. Social media is expanding at present and becoming important in society. Social network sites allow users to communicate with people in the network by sharing posts, images, videos, status. The proposed system gathers the information from the social media websites and performs the sentiment analysis on the social media data using GPU. The work concentrates on recognizing the sentiment information from the text reviews and using that to identify the items. The aim of this paper is to do analytics on social media data. Analysis is done on the data using K Nearest Neighbor algorithms and Support Vector Machine algorithm on the GPU.

Authors and Affiliations

Harshita Mandloi
School of Computer Science and IT, DAVV, Indore, Madhya Pradesh, India
Shraddha Masih
School of Computer Science and IT, DAVV, Indore, Madhya Pradesh, India

Parallel Computing, GPU, Social media, K nearest neighbor, SVM

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Publication Details

Published in : Volume 3 | Issue 6 | July-August 2018
Date of Publication : 2018-07-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 428-434
Manuscript Number : CSEIT183687
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Harshita Mandloi, Shraddha Masih, "Sentiment Analysis Using Parallel Computing Through GPU", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 6, pp.428-434, July-August-2018.
Journal URL : http://ijsrcseit.com/CSEIT183687

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