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On Building a “Fake News” Classification Model *update

On Building a “...

“A lie gets halfway around the world before the truth has a chance to get its pants on.” – Winston Churchill Since the 2016 presidential election, one topic dominating political discourse is the issue of “Fake News”. A number of political pundits claim that the rise of  significantly biased and/or untrue news influenced the election, though a study by researchers […]

Changes in Turnout and Preference

Changes in Turnout a...

Editor’s note: Opinions expressed in this post do not necessarily reflect the views of #ODSC So, as you know, Hillary Clinton narrowly lost the Electoral College and probably narrowly won the popular vote. And there’s lots of theorising about how these huge swings came about and what they mean. An important first step is to think about how […]

What Donald Trump and Biased Polls Can Teach Us About Data

What Donald Trump an...

Pity the pollster.  As the election cycle mercifully nears its inevitable end, cries of bias from the trailing party will grow louder, and a sport played for well over a hundred years, calling statistics lies, reaches fever pitch. Donald Trump is, of course, correct. Survey polls are biased.   Bias is certainly nothing new to […]

Analyzing the Election: Deciding for Yourself

Analyzing the Electi...

Editor’s note: Opinions expressed in this post do not necessarily reflect the views of #ODSC It’s election season and everyone, everywhere is prognosticating who will win, why someone may lose. Gathering data to analyze how you and I are feeling in order to make these predictions and determine the best course of action for political parties and their […]

Debate Night Twitter Part 2: Analyzing the Tweets of the Final Debate.

Debate Night Twitter...

Editor’s note: Opinions expressed in this post do not necessarily reflect the views of #ODSC Last Wednesday, the third and final debate of the 2016 Presidential Election was held and with three weeks to go before election day, the two candidates sought to persuade undecided voters and rally their supporters in another tense head-t0-head matchup. As we did for the […]

Text Mining Trump Speeches Part 3: Topic Modeling, Trump fixated on Hillary

Text Mining Trump Sp...

Editor’s note: Opinions expressed in this post do not necessarily reflect the views of #ODSC At the start of this blog series I had no idea how the campaign dialogue would evolve.  I am surprised how the discussion has distanced even farther from issues to personal affairs leaving many Republicans to abandon Donald Trump altogether.  The dialogue has […]

Debate Night Twitter: Analyzing Twitter’s Reaction to the Presidential Debate.

Debate Night Twitter...

Editor’s note: Opinions expressed in this post do not necessarily reflect the views of #ODSC This past Sunday, Donald Trump and Hillary Clinton participated in a town hall-style debate, the second of three such events in this presidential campaign. It was an extremely contentious affair that reverberated across social media. The political showdown was massively anticipated; the negative atmosphere […]

Trump and Clinton Speeches, Step 2: Trump is a Negative Sophomore and Clinton is a positive one!

Trump and Clinton Sp...

Editor’s note: Opinions expressed in this post do not necessarily reflect the views of #ODSC, nor do they necessarily reflect the views of Edward’s employer. Looks like the presidential race is heating up!  Many polls have the candidates in a tight race.  Just after the debate both Clinton and Trump proclaimed “victory.” Instead of sound bites in this […]

Election Manipulation Through Data Visualization

Election Manipulatio...

While verbal communication is a necessary skill for any data scientist, visual communication is becoming more important for maximizing impact. Viz is hard, it requires a different skillset and recognition that your design choices can manipulate the story. As Data Scientists drift into the forbidden realms of artistic expression, I’m engrossed by the question “How […]