TY - GEN
T1 - CashTagNN
T2 - 4th International Conference on Algorithms, Computing and Systems, ICACS 2020, held jointly with the 2nd African Electronics, Computer and Communication Conference, ICACS-AECCC 2020
AU - Rajesh, Neeraj
AU - Gandy, Lisa
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/1/6
Y1 - 2020/1/6
N2 - In this paper, the authors present a system, CashTagNN, which uses the sentiment and subjectivity scores of tweets that include cashtags to model stock market movement, and in particular, predict opening stock market prices. Currently, the system focuses on two companies: Apple and Johnson \ Johnson. The system uses two machine learning methods for prediction, a feed-forward neural network, and a deep convolutional neural network. The authors use stock market prices in March and October 2016 as training data, with stock market prices in November 2016 as test data. The time series used for training and testing consists of stock prices recorded at one minute, five minutes, and one-hour intervals. Results show that the Feed Forward Network Model, in this case, outperforms the Deep Convolutional Network model.
AB - In this paper, the authors present a system, CashTagNN, which uses the sentiment and subjectivity scores of tweets that include cashtags to model stock market movement, and in particular, predict opening stock market prices. Currently, the system focuses on two companies: Apple and Johnson \ Johnson. The system uses two machine learning methods for prediction, a feed-forward neural network, and a deep convolutional neural network. The authors use stock market prices in March and October 2016 as training data, with stock market prices in November 2016 as test data. The time series used for training and testing consists of stock prices recorded at one minute, five minutes, and one-hour intervals. Results show that the Feed Forward Network Model, in this case, outperforms the Deep Convolutional Network model.
KW - Convolutional Networks
KW - Feed Forward Neural Networks
KW - Social Media
KW - Stock Market Prediction
UR - http://www.scopus.com/inward/record.url?scp=85097336200&partnerID=8YFLogxK
U2 - 10.1145/3423390.3423392
DO - 10.1145/3423390.3423392
M3 - Conference contribution
AN - SCOPUS:85097336200
T3 - ACM International Conference Proceeding Series
SP - 1
EP - 5
BT - Proceedings of ICACS 2020 - 4th International Conference on Algorithms, Computing and Systems - ICACS-AECCC 2020 - 2nd African Electronics, Computer and Communication Conference
PB - Association for Computing Machinery
Y2 - 18 September 2020 through 20 September 2020
ER -