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Stock prediction through Twitter sentiment analysis & Natural Language Processing
Our forecasting methodology is: To analyze and categorize the twitter sentiment regarding Daimler company (positive, newtral, negative) and then analyze to see if there is a correlation between the sentiment and the share price.
The benefit of this methodology is that we can receive the tweets real time and we can make our corresponding corrections on our portfolio
If there is a correlation between the daily price change and the sentiment score of our target share, we could predict the next day’s movement.
Of course our models here can be applied in any kind of opinion measurement. Not only for shares forecasting. Marketing is a domain with many applications of that kind of analysis. More than one billion users are sending and reading “tweets”
ANLY 540-51 Assignment 2
ANLY 540-51-A-2019/SummerANLY 540-51- A-2019/Summer - Analysis of the Human Language
Reproducible Research: Course Project 2
Exploring the NOAA Storm Database to identify the impacts of severe weather events.
Linear Regression: Interaction Effects
Seminar script for the Data Analysis in Sociology 2019 class