TY - JOUR
T1 - CashTagNN: Using sentiment of tweets with CashTags to predict stock market prices
AU - Gandy, Lisa
AU - Rajesh, Neeraj
N1 - In this paper we discuss a system, CashTagNN, which uses the sentiment and subjectivity scores of tweets that include cashtags of two companies, Apple and Johnson and Johnson, to model stock market movement, and in particular predict opening and closing stock market prices.
PY - 2016/10/8
Y1 - 2016/10/8
N2 - In this paper we discuss a system, CashTagNN, which uses the sentiment and subjectivity scores of tweets that include cashtags of two companies, Apple and Johnson and Johnson, to model stock market movement, and in particular predict opening and closing stock market prices. We demonstrate that by using only sentiment and subjectivity along with a neural network machine learning model we can predict the opening and closing prices of the two companies with high accuracy.
AB - In this paper we discuss a system, CashTagNN, which uses the sentiment and subjectivity scores of tweets that include cashtags of two companies, Apple and Johnson and Johnson, to model stock market movement, and in particular predict opening and closing stock market prices. We demonstrate that by using only sentiment and subjectivity along with a neural network machine learning model we can predict the opening and closing prices of the two companies with high accuracy.
UR - https://ieeexplore.ieee.org/abstract/document/7772262
U2 - 10.1109/SITA.2016.7772262
DO - 10.1109/SITA.2016.7772262
M3 - Article
JO - IEEE Xplore
JF - IEEE Xplore
ER -