Tweets Miner for Stock Market Analysis
Bohdan Pavlyshenko
TL;DR
This paper introduces an R-based software package that mines Twitter data to analyze stock market trends by comparing keyword frequency with stock charts.
Contribution
It presents a novel R package for mining Twitter data specifically tailored for stock market analysis, including keyword frequency analysis and chart comparison.
Findings
Twitter keyword trends correlate with stock market movements
The R package effectively extracts relevant microblog data
Preliminary results show potential for predictive analysis
Abstract
In this paper, we present a software package for the data mining of Twitter microblogs for the purpose of using them for the stock market analysis. The package is written in R langauge using apropriate R packages. The model of tweets has been considered. We have also compared stock market charts with frequent sets of keywords in Twitter microblogs messages.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Text Analysis Techniques · Complex Network Analysis Techniques · Stock Market Forecasting Methods