The Political Power of Words
Searching for meaning in 280 characters or less
It was the Lebanese-born poet and painter, Kahlil Gibran, who once uttered, “all our words are but crumbs that fall down from the feast of the mind.”
They are thoughts thrust into existence. Actions have claimed to speak louder, the pen mightier, but true power continues to lay with the word; in its capacity to inspire and motivate, to denigrate and condemn.
As part of my computer programming course at the PDX Code Guild, we were recently tasked with constructing a project to signal the shift of focus from the back-end to the front-end; from the approachable language of Python to the upcoming structure and artistry of HTML & CSS.
The first few hours of contemplation were a struggle; a constant scene of head on desk, as I lingered in search of an idea at least partially unique. To my surprise and satisfaction, one ultimately came, and then the next.
From politics to food to sports, potential plans were jotted into a Google Doc as quickly as my fingers could mash the keys. Some earned metaphorical pins for a later date; others shuffled over to a “just for fun” pile, where I could tinker and toy without concern over deadline or significance.
There was one, however, which stuck out. It felt timely and necessary. A series of visual snapshots, targeting the curated minds of those who wish to lead us into the new decade. Those who vie for the top prize in a year when hindsight should be at its most formidable, yet will no doubt languish in nebulosity.
The settled upon name for the project was “poliplotter”; a tool designed to generate word clouds based on Twitter data. The roots of the designation stem from “poli,” with its reference to politics, and “plotter,” as in to mark on a graph or chart.
The targets for the experiment, at least in the short-term sense, were the 2020 Democratic hopefuls for president. More specifically, the top five vote-getters, as per the polls at the time of this posting. Sorry, Beto.
The objective was to sift through the crowded field and offer a measure of clarity on the candidates; to provide a lens into their priorities and filter their focus, as best communicated with their own words.
The images presented below are the results, mapped against the outlines of the candidates, as they state their cases from various stages across America; the flag a familiar backdrop.
Each word cloud represents one thousand of their most recent tweets, which account for roughly three months of activity. Beneath the images, my best summarizations of the findings.
Note: I am accepting of feedback. If you are in disagreement with any of my assessments, please feel free to comment and let me know, but do keep it respectful. I’m open to measured discussions, not tantrums.
Joe Biden
The former vice-president is the plan guy. He speaks of America, of the people, of togetherness. The rural communities are a focus; helping reclaim work and opportunity, dignity and power. Attention is given to health care and, of course, Trump.
Bernie Sanders
The man of the people. No surprise, Medicare is a central theme to his message. The senator wants to fight for the American worker; to provide health care as a right, along with a living wage. And he is not shy about calling out the president.
Elizabeth Warren
The senator from Massachusetts has been clear. She will fight to break up the big tech companies, alleviate student debt and protect the American workers. Through legislation, she has taken aim at reigning in Wall Street and helping families.
Kamala Harris
The former attorney general of California walks the walk. Her message is somehow both varied and consistent. She owns her identity and continues the fight for justice; for teachers, for communities, for families, for the American people.
Pete Buttigieg
The youngest of the 2020 hopefuls, Mayor Pete knows the time is now. He separates himself by staying focused on the climate, yet devoted to the American workers. His plans promote equality and adaptation to the changing economy.
Words — so innocent and powerless as they are, as standing in a dictionary, how potent for good and evil they become, in the hands of one who knows how to combine them! — Nathaniel Hawthorne
A few closing notes:
- To achieve the above results, a number of different libraries were imported into my Python code, ranging from tweepy and numpy to matplotlib, textblob and wordcloud. Clearly, absurd names to any of those outside of the dev community, but they sure were helpful!
- In addition, certain items, such as retweets, special characters and stopwords, were removed for the purpose of clarity and concentration.
- Lastly, the placement of each word within the images were performed at random and were not self-adjusted in any way.
Originally published at http://www.mjhughes.io on July 28, 2019.
