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Test Notebook.ipynb

Test Notebook.ipynb

 
 

candidateFilter.py

candidateFilter.py

 
 

config.py

config.py

 
 

helper.py

helper.py

 
 

model.py

model.py

 
 

reader.py

reader.py

 
 

senti.py

senti.py

 
 

sentimentPMI.py

sentimentPMI.py

 
 

stateSplit.py

stateSplit.py

 
 

test.py

test.py

 
 

topic.py

topic.py

 
 

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Model the US 2012 general election result using probability risk analysis technique with Twitter released data.

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natural-language-processing sentiment-analysis modeling probability python3 election-polling
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