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It’s understandable if you missed Reddit’s Super Bowl commercial tonight; it was only five seconds long. The majority of the commercial was a text message that would have been difficult to decipher in the heat of the moment, saying that the company had expended its “entire marketing budget on five seconds of airtime.”
Reddit explains, “One thing we learned from our communities last week is that underdogs can achieve something when they come together behind a shared concept,” a direct reference to the GameStop stock saga, which was fueled by posters on the r/WallStreetBets subreddit. “Who knows, maybe you’ll be the one who forces finance textbooks to have a chapter on ‘tendies.’”
We couldn’t afford to buy a whole one because big game spots are too costly. But we were so moved that we wanted to spend the entirety of our marketing budget on 5 seconds of airtime. Last week, we heard from our groups that underdogs can do everything if they band together around a common goal.
Perhaps you’ll be the reason finance textbooks ought to include a chapter on “tendies.” If you can assist r/SuperbOwl in educating the world about the majesty of owls. Perhaps you’ll even pause this 5-second commercial.
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This article details the implementation of a data scraping and natural language processing project that consisted of two parts: scraping as many posts as possible from Reddit’s API, and then using classification models to predict the posts’ roots.
A Reddit post classification was the third project I had to complete during my data science immersion. We’d just finished data scraping and natural language processing, so the project was split into two parts: scrape as many posts as possible from Reddit’s API, and then use classification models to guess where the posts came from.
I finished the project a while ago, but I wanted to revisit it now that I’ve gained more experience: I’ve learned about two new classification models since then (support vector classifier and XGBoost classifier).
Since they don’t need a key to access the API, scraping data from Reddit’s API is fairly simple: it’s just a straightforward request set up. Fortunately for me, I still had the first set of posts from when I first finished this project, which totaled about 4,000.
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According to Alexa Internet, Reddit is the 18th most-visited website in the world and the 7th most-visited website in the United States as of February 2021.
Analyzing millions of early reddit submissions
[number six] The United States accounts for 42-49.3 percent of its user base, followed by the United Kingdom at 7.9-8.2 percent and Canada at 5.2-7.8 percent. [nine] [number six]
In 2005, Steve Huffman and Alexis Ohanian, then college roommates, came up with the concept and the first version of Reddit. During their spring break from the University of Virginia, Huffman and Ohanian attended a lecture by programmer-entrepreneur Paul Graham in Boston, Massachusetts. [number 16] (17) [nineteen] Following the lecture, Graham approached Huffman and Ohanian and invited them to apply to his startup incubator, Y Combinator. [number 16] Their first concept, My Mobile Menu, was a flop, so they came up with a new one.  It was created with the intention of allowing users to order food through SMS text messaging. [number 16]  During a brainstorming session for another startup, Graham came up with the concept for the “front page of the Internet.” Huffman and Ohanian were admitted into Y Combinator’s first class for this concept. [number 16] (17) With support from Y Combinator, Huffman coded the web in Popular Lisp and co-founded Reddit with Ohanian in June 2005. [number 23] [page 24]
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It’s the go-to social news and debate site today, with over 26 million active users. You’re missing out on a wealth of breaking news and some really fascinating discussions if you don’t use Reddit.
Craig has extensive experience in the technology and gaming industries as a blogger, coder, and marketer. Since 2008, he’s worked remotely for some of the industry’s most prestigious magazines, specializing in Windows, PC hardware and software, automation, and other topics. Craig’s full bio can be found here.