2. Introduction • Problem / Question?
– How is DonaldTrump’s popularity getting affected due to his
recent immigration policy?
– Are there any other implications?
• Data Source
– Twitter feed
• Solution
– SentimentAnalysis of twitter data
– Frequency analysis of words
• Tools
– Python – programming language
– API –Twitter API
– Packages – json, time, tweepy, nltk, textblob etc.
Introduction Data Collection Analysis Conclusion
3. Timeline
of
Travel
Ban
• Friday, Jan. 27
• Trump signs executive order on immigration
• An unknown number of other American citizens from a
few countries were detained
• Saturday, Jan. 28
• Protests begin
• ACLU’s request for a nationwide temporary injunction
• Poll
• Majority opposeTrump's travel ban
• Saturday, Feb. 4
• Homeland Security suspends travel ban
Introduction Data Collection Analysis Conclusion
4. How
We
Collected
the
Data
• Key Words (4 keys)
– Trump
– Ban
– Immigration
– Halt
• Data Set
– 19,000 + tweets across four keywords
• Location
– Global data
• Language
– Only English
• Data Cleansing (NLTK pkg)
– Filter stop words
• What we did not collect
– Did not put ‘#’ before keywords to avoid limiting search
Introduction Data Collection Analysis Conclusion
6. People’s
Attitudes
toward
Trump
• President
• Donald
• Wall
• Judge
• Saying
• Political
• Republicans
• Terrorist
• Ban
• White
• Infuriating
• Protect
• attack
Introduction Data Collection Analysis Conclusion
Frequency Analysis
And
Word Cloud
12. Introduction Data Collection Analysis Conclusion
People’s
Attitudes
toward
the
Halt
• Travel
• Ban
• Judge
• Security
• Country
• Coming
• Homeland
• Bad
• Intention
• Trump
• Court
• Rejects
• Overturn
• Immigration
Frequency Analysis
And
Word Cloud
15. Introduction Data Collection Analysis Conclusion
Conclusion • The policies have certainly impacted
his popularity
• Analysis indicative of impact
• Indirect implications
– Implementation of stricter immigration
policy will affect the global economy and
not just US