Stock Prediction Using Twitter Sentiment Analysis
By A. Mittal. 2011
308 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/4ecc55e1c3ff1cee41f21e5b0a3b22c58d04c9d6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
Citations in the corpus
- Stock closing price prediction based on sentiment analysis and LSTM (2019, background): “…it is generally accepted that stock market prices are largely driven by new information and follow a random pattern, many studies have shown the effectiveness of predicting stock market behavior based on behavioral economics that emphasizes the important role of emotion in decision making [26, 27].”
- Sentiment analysis of Twitter data for predicting stock market movements (2016, methodology): “The missing data is approximated using a simple technique by Goel [17].”
- Twitter brand sentiment analysis: A hybrid system using n-gram analysis and dynamic artificial neural network (2013, background): “Researchers have also utilized Twitter as a source of information to explain and predict movements in stock markets and other socioeconomic indicators (Bollen, Mao, & Zeng, 2011; Bollen, Pepe, & Mao, 2011Bollen, Pepe, & Mao, 2011; Mittal & Goel, 2012).”