A case from State Street, which turned out useless in our hands. At least now I know how to do it.

1. Economy Overview Based
on Twitter Sentiment Analysis
DI SU
TATIANA IVANOVA
FATEMEH DAVARZAN
MANOUCHEHR YOUSEFSIBDARI
HITESH KUMAR

2. Introduction
• Goals:
1. Define financial topic for research
2. Analyze data from Twitter
3. Design a report, that contain relevant financial information for a
story in a condensed format

3. Methodology
 Authorization
 Extracting tweets
 Cleaning tweets
 Sentiment analysis
 Visualization

4. Authorization

5. Extracting Tweets
Number of tweets
Russia 4,000
USA 4,000
China 3,500
Iran 3,000
India 3,000
Total 17,500

6. Cleaning Tweets

7. Sentiment Analysis

8. Visualization
Russia
Emotional Classification
Code

9. Visualization
Russia
Polarity Classification
Code

10. Plot and Histogram Code

11. Visualization
Russia
Plot Histogram

12. Visualization
Russia
Word Cloud Code

13. Visualization
China
Emotional Classification Polarity Classification

14. Visualization
China
Plot
Histogram
Word Cloud

15. Visualization
USA
Emotional Classification Polarity Classification

16. Visualization
USA
Plot Histogram
Word Cloud

17. Visualization
Iran
Emotional Classification Polarity Classification

18. Visualization
Iran
Plot Histogram
Word Cloud

19. Visualization
India
Emotional Classification Polarity Classification

20. Visualization
India
Plot Histogram
Word Cloud

21. Economy General Overview
2. Dataset

22. Dataset Code

23. Economy General Overview
1. Word Cloud Comparison

24. Word Cloud Comparison Code
Cleaning tweets
Visualization

25. Future improvements
 Text Mining Improvements
 Cleaning for Word Cloud
 Sentiment Analysis for Oil Price (Optional)