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Social network news sentiments and stock price movement: a correlation analysis
Anupong Sukprasert1, Kasturi Kanchymalay2, Naomie Salim3, Atif Khan4.
The stock market prediction is one of the most important issues extensively investigated in the existing academic literatures. Researchers have discovered that real–time news has much bearing on the movement of stock prices. Analysts now have to deal with vast amounts of real time, unstructured streaming data due to the advent of electronic and online news sources. This paper aims to investigate the relationship between online news and actual stock price movement. R programming together with R package are applied to capture and analyze the online news data from Yahoo Financial. The data are plotted into graphs to analyze the relationship between the two variables. In addition, to ensure the levels of the relationship, the Pearson’s correlation and Spearman’s Rank are applied to test whether there is a statistical association between these two variables. This initial analysis of dynamic online news based on sentimental words is relatively constructive.
Affiliation:
- Mahasarakham University, Thailand
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknologi Malaysia, Malaysia
- Universiti Teknologi Malaysia, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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