Journal of Intelligent Marketing Management

Journal of Intelligent Marketing Management

Predicting the market influenced by consumer sentiments using artificial intelligence

Document Type : The scientific research paper

Authors
Avaz Naghipour 1
Elham Baghbani 2
1 Department of Computer Engineering, University College of Nabi Akram,Tabriz, Iran
2 Department of Computer Engineering, University College of Nabi Akram, Tabriz, Iran
JABM.3.2.15564.351256.3257456
Abstract
Because of the non-linear fluctuations of the stock price, it is challenging to predict. Therefore, it is important to identify the characteristics that can be used to predict market behavior. Both traditional and modern methods are very important for these features. Among these features, we can mention the feelings and emotions of consumers. In this research, the effect of consumer sentiment factor in predicting market fluctuations has been investigated. For this purpose, the S&P500 index has been considered for forecasting first without considering the characteristics of consumer sentiments using BiLSTM deep neural network and then by combining the UMCSENT consumer sentiment factor. The experiments and results of this research show that the use of consumers' feelings and emotions increases the accuracy of forecasting the S&P500 index.
Keywords
Deep Learning
Neural Network
Stock Price
Consumer Sentiment
UMCSENT

Subjects

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  • Receive Date 19 October 2024
  • Revise Date 01 November 2024
  • Accept Date 01 November 2024