Twitter's Role in Data Science

As data science enthusiasts, we hear about Twitter’s role in web scraping and sentiment analysis in various projects and research journals. Twitter gives us a constant influx of data on any topic imaginable, giving analysts a way to generate reports on how people feel about healthcare, the stock market, or even the newest addition to the menu at a fast food chain. The options are endless. However, from following dozens of data scientists over the course of a year, I’ve found that Twitter is more than just a website to pool data from.
In fact, Twitter is partially how I became interested in data science. It started when I followed FiveThirtyEight, a website that publishes opinion poll analytics in politics, economics, and sports. I’m the type of person who checks the comments on any YouTube video, cooking blog, or news article, so I, of course, had to check the replies to these Tweets that FiveThirtyEight sent out. In the thread, I found numerous interactions between data scientists who shared their critiques on the analysis or who brought up important issues like data visibility or bias. 
Such discussions made me realize how data science has more depth to it than I thought, and knowing the nuances of the field piqued my interest. I wanted more of these insights on my feed, so I started to follow accounts of individuals who contributed a lot on Twitter threads about data science. From following a few of these individuals, I started getting more data science tweets on my feed and becoming interested in this field.
Now, articles about new packages that are coming out in R, new ways to create stunning and informative visualizations, and data science ethics all pop up on my Twitter feed. I have an endless stream of articles and discussions that keep me updated and engaged. 
One of my favorite trends to follow is the tag #tidytuesday, a weekly data challenge that numerous individuals attempt whether they’re showing off their prowess in R, or just trying to learn it. In fact, I got my visualization for Communications Training from a #tidytuesday challenge, in which users were given a dataset of ramen noodle ratings by country!