Conversely, if a subreddit contains a number of comments made only by a single individual or by individuals who only post in that subreddit and not in others, then it too can be seen of little influence, as very few people are involved or interested in discussion of those concepts. If a subreddit is seen by many but participated in by only a few, then it can be said that the subreddit is of little influence, as the subject material is not of enough importance to be debated or even backed by followers. Because posters actually create original content and provide feedback on other posters through comments, they generate the bulk of the influence of a subreddit. Let a poster be someone who has created an account on Reddit and has actually written up and submitted a comment to a subreddit these contrast with lurkers, those who have an account on Reddit and frequent certain subreddits, but who never actually provide original content themselves. We can measure the similarities between two subreddits based on a simple metric I’ve used throughout this project. Though originally all years and months’ worth of data was to be used in analysis, only data since late 2011 (directly following the election of Barack Obama for his second term) was deemed of a large and high enough quality to make analyses. This amounted to around 850 GB of data, though for the purpose of this project, only about half of that was used. From these, the comments were extracted and converted from their original format to a CSV format that could more easily be saved and analyzed using Pandas. The data was originally received in month-by-month compressed JSON files of all Reddit comments given that month. To complete this project, I downloaded the entirety of the Reddit comment corpus for free from Jason Baumgartner’s pushshift.io (though also consider donating to him in thanks for maintaining his resources and for sharing them all freely with the public). By comparing the individuals between subreddits, we can see how closely their bases are to each other therefore, we can visualize relationships between subreddits based on their followers. These subreddits, when isolated, paint a clear picture of the types of individuals who participate in them. Subreddits range in topic from user hobbies like handbells and kayaking to adherence of ideologies like economics and anarchism. Additionally, the site is further subdivided into thousands of communities each dedicated to a specific topic or purpose, known as subreddits. With the purpose of providing a medium where users can semi-anonymously share ideas and content, Reddit is a perfect testing ground for gathering data on individuals and groups and the beliefs held by both. Reddit is an online social platform netting millions of American users each day. Trump winning the majority of the Electoral College and hence becoming the 45th President of the United States was an outcome which at the time I had thought impossible, if solely due to the aforementioned eccentric series of events that had circulated around Trump for a majority of his candidacy.įollowing the election, the prominent question that could not leave my mind was a simple one: how? How had the American people changed so much in only a couple of years to allow an outsider hit by a number of black marks during the election to be elected to the highest position in the United States government? How did so many pollsters and political scientists fail to predict this outcome? How can we best analyze the campaigns of each candidate, now given hindsight and knowledge of the eventual outcome? In an attempt to answer each of these, I have turned to a perhaps unlikely source. However, the finale of the election that culminated with Republican candidate Donald J. So much happened during the months leading up to November that it became difficult to keep track with what who said when and why. The 2016 Presidential Election was, in a single word, weird. This article was written for The Data Incubator by Jay Kaiser, a Fellow of our 2018 Winter cohort in Washington, DC who landed a job with our hiring partner, ZeniMax Online Studios, as a Big Data Engineer.
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