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Students attending SUNY at Buffalo collecting and analyzing many sources of information to quantify and visualize the 2016 US presidential election

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Election and Data Science

We extracted and visualized relevant data of 2016 and past US President Election.

All of our works are present in these website:

http://96.243.34.179/index.html (twitter live stream added)


To explain about the details of the website, it has four different tabs: Home, Data, Twitter Analysis, and Speech.
  • Home

Home page is filled by Donald Trump's big picture with our team's name. Donald Trump deserves to be in the main page as he won 2016 US President Election
  • Data

Data tab shows 5 different tabs for each Election year since 2000. If you click the tab of any year, it will show the US Map with red or blue colors with different shade.
The darker red shade, the more Republican poll results and the darker blue shade, the more Democratic poll results. If you hover any State, it will show the poll results of the State between Republican and Democratic.
2016 tab is a bit more special as it shows all aggregated poll results since 2000 by hovering, and if you click the State, it will direct you to a new webpage showing the poll results as well as the colored county map.
  • Twitter Analysis

Twitter analysis tab has the data visualizations and analysis of data collected from Twitter. The twitter data collected consisted of mentions of the presedential candidates in a good and neutral way from each state. The data was plotted in a graph for each candidate to come to conclusions on general opinion of the nation.
  • Speech

Shows visual graphs of analysis of the whole past Presdients' speech. We counted the number of words for specific important words they spoke, and how many words there are in each sentence on average.
  • Live Stream

The Live Sream tab shows a live Twitter feed of positive sentiment tweets regarding Donald Trump and the historical counts of those positive tweets. This live stream is consistent proof that an algorithm can constantly filter polarizing tweets.

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Students attending SUNY at Buffalo collecting and analyzing many sources of information to quantify and visualize the 2016 US presidential election

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