-Chazz Inniss, Cory Fernandez, Cameron Jenkins
The latest epidemic to American media is not reality television, but rather started by reality television, is #fakenews. Spewed out by venomous trolls like Donald Trump, KellyAnne Conway and Sean Spicer, #fakenews has led to distrust of American press and has further spread the schism between politicians and the public. Since, people turn to social media for the news and for the spreading of news, the outpour of discussion on the topic comes as no surprise.
Liberals like Chris Matthews and the #FakeNews propagandists at CNN believe blacks are too stupid to get an i.d.! pic.twitter.com/VK0NlO1QSh
— Josh Cornett (@therealcornett) January 27, 2017
On Sysomos MAP 2.0, the most retweeted tweet is the one above with 9983 retweets. This tweet had major engagement on Twitter throughout the Conservative social media atmosphere.
With about 1.2 million Twitter results using the hashtag, #FakeNews, the discussion remained heated and engaging throughout the month of January.
At it’s peak: #FakeNews spread like rapid fire on January 11, with a grand total of 168.3k Tweets using the #FakeNews hashtag that day. The hashtag started to gain traction closer to the inauguration, reaching it’s peak on the 11th when news of Russia having compromising information on Donald Trump. After this date, it remained steady with small periodic jumps.
How far the epidemic spread: #FakeNews had most of it’s influence in the United States with 75.8% of the tweets coming from that part of the world. The rest of the world was also engaging in the conversation minimally.
Words used: So the discussion was based around numerous different words to describe people’s thoughts and feelings. The conversation revolved mostly around the words “Fake,” “Donald,” “news,” “Trump,” and also some other words like “Russia,” and “intelligence. Most of the words linked Donald Trump with fake news and also with CNN.
In our analysis of #FakeNews on Twitter, we dug up a lot of interesting information. Aside from the massive 168.3k tweets that surfaced, the data provided a considerable amount of insight into how “fake news” has functioned in the Twittersphere.