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Automated Trading of Cryptocurrency Using Twitter Sentimental Analysis

S.R. Chheda1 , A.K.Singh 2 , P.S. Singh3 , A.S. Bhole4

  1. Dept. of Computer Science and Engineering, Ramdeobaba College of Engineering and Management, Nagpur, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-5 , Page no. 209-214, May-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i5.209214

Online published on May 31, 2018

Copyright © S.R. Chheda, A.K.Singh, P.S. Singh, A.S. Bhole . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S.R. Chheda, A.K.Singh, P.S. Singh, A.S. Bhole, “Automated Trading of Cryptocurrency Using Twitter Sentimental Analysis,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.209-214, 2018.

MLA Style Citation: S.R. Chheda, A.K.Singh, P.S. Singh, A.S. Bhole "Automated Trading of Cryptocurrency Using Twitter Sentimental Analysis." International Journal of Computer Sciences and Engineering 6.5 (2018): 209-214.

APA Style Citation: S.R. Chheda, A.K.Singh, P.S. Singh, A.S. Bhole, (2018). Automated Trading of Cryptocurrency Using Twitter Sentimental Analysis. International Journal of Computer Sciences and Engineering, 6(5), 209-214.

BibTex Style Citation:
@article{Chheda_2018,
author = {S.R. Chheda, A.K.Singh, P.S. Singh, A.S. Bhole},
title = {Automated Trading of Cryptocurrency Using Twitter Sentimental Analysis},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {6},
Issue = {5},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {209-214},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1964},
doi = {https://doi.org/10.26438/ijcse/v6i5.209214}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i5.209214}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1964
TI - Automated Trading of Cryptocurrency Using Twitter Sentimental Analysis
T2 - International Journal of Computer Sciences and Engineering
AU - S.R. Chheda, A.K.Singh, P.S. Singh, A.S. Bhole
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 209-214
IS - 5
VL - 6
SN - 2347-2693
ER -

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Abstract

Twitter is one of the most used social networking sites where millions of people give their opinions about various subjects. Thus it can be treated as one of the largest and most updated psychological database. Analysis can be performed on this data to gain valuable insights. The goal of this paper is to study the correlation between public opinion about the Cryptocurrency, Bitcoin and the trajectory of its price graph. The results can later be used to develop a system for algorithmic trading of Bitcoin. This is done by collecting tweets on bitcoin and performing sentimental analysis on it. The tweets are labelled positive or negative. Supervised machine learning algorithms are used to see how sentiments of tweets play a role in bitcoin market movement. A positive sentiment and an increase in the price of bitcoin at the same time will indicate selling as favourable and vice versa in case of a negative polarity of tweets.

Key-Words / Index Term

Twitter, opinions, sentimental analysis, bitcoin, machine learning algorithms

References

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