A Comprehensive Review of Stock Price Prediction Using Text Mining

Maede TajMazinani, Hosein Hassani and Reza Raei
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Maede TajMazinani: Department of Finance and Insurance, University of Tehran
Hosein Hassani: Research institute for energy management and planning, University of Tehran
Reza Raei: Department of Finance and Insurance, University of Tehran

Advances in Decision Sciences, 2022, vol. 26, issue 2, 116-152

Abstract: Purpose- In various studies, the sentiment analysis identifies as an essential part of stock price behavior prediction. The availability of news, social media networks, and the rapid development of natural language processing methods resulted in better forecasting performance. However, there is a lack of a comprehensive framework and review paper to address the advantages and challenges of this very timely topic. Design/methodology/approach- This paper aims to promote the existing literature in this field by focusing on different aspects of previous studies and presenting an explicit picture of their components. We, furthermore, compare each system with the rest and identify their main differentiating factors. This paper summarized and systematized studies that seek to predict stock prices based on text mining and sentiment analysis in a systematic review paper. Findings- It discussed the developments made during recent years and addressed the existing gap in this field to the research community.

Keywords: Stock price prediction; Sentiment analysis; Text mining; Big data (search for similar items in EconPapers)
Date: 2022
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