Twitter

8 posts
Visualizing Verified Twitter’s Reaction to Robert Mueller’s Investigation

Special Counsel Robert Mueller’s now-concluded investigation into the Trump campaign and Russian influence over the 2016 presidential election was obviously a hot topic on Twitter. More than 400,000 tweets — an average about 600 per day — mentioned the word* “Mueller” since the former FBI chief was appointed to lead the investigation in May 2017, according to a dump (190MB csv) of verified user data pulled from the social network using Python...

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Visualizing a Year of @realDonaldTrump

President Trump thumbed his way through another year in the White House while staying busy on Twitter, compiling a good (great) collection of 2,930 touts, complaints, defenses and rants. He left 2018 with this perplexing New Year’s Eve missive extolling the old-fashioned endurance of “Walls” and “Wheels” as one of his last. As the message shows, the president’s twitter presence lately is crowded by an increasingly evergreen list of grievances...

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How a meme grew into a campaign slogan

A meme that cried “jobs not mobs” began modestly, but a couple of weeks later it found its way into a slogan used by the President of the United States. Keith Collins and Kevin Roose for The New York Times traced the spread of the meme through social media using a beeswarm chart. Blue represents activity on Twitter, yellow represents Facebook, and orange represents Reddit. Circles are sized by retweets,...

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Visualizing the toxicity in Twitter conversations

Peter Beshai was tasked with visualizing the toxicity in Twitter conversations. He arrived at this organic-looking model using 3-D visual effects software. Nice. Tags: toxic, Twitter

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Download 3 million Russian troll tweets

Oliver Roeder for FiveThirtyEight: FiveThirtyEight has obtained nearly 3 million tweets from accounts associated with the Internet Research Agency. To our knowledge, it’s the fullest empirical record to date of Russian trolls’ actions on social media, showing a relentless and systematic onslaught. In concert with the researchers who first pulled the tweets, FiveThirtyEight is uploading them to GitHub so that others can explore the data for themselves. The data set...

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Twitter bot purge

With Twitter cracking down, some users are experiencing bigger dips in follower count than others. Jeremy Ashkenas charted some of the drops. Tags: fake, Twitter

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Changing Twitter, with Statistics

Earlier this year, The New York Times investigated fake followers on Twitter showing very clearly that it was a problem. It’s hard to believe that Twitter didn’t already know about the scale of the issue, but after the story, the social service finally started to work on the problem. Nicholas Confessore and Gabriel J.X. Dance for The New York Times: An investigation by The New York Times in January demonstrated...

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Tweeting a map of every Census tract in the United States

By Neil Freeman, the @everytract bot on Twitter, as the name suggests, is tweeting a map of every Census tract in numerical order. It’s one map each half hour. Census data, or data in general really, is typically in aggregate or about the overall trends, which requires an abstract view of a bunch of data points pushed together. So it’s nice to see a straightforward project put focus on the...

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Bot or Not: A Twitter user classifier

Michael W. Kearney implemented a classifier for Twitter bots. It’s called botornot: Uses machine learning to classify Twitter accounts as bots or not bots. The default model is 93.53% accurate when classifying bots and 95.32% accurate when classifying non-bots. The fast model is 91.78% accurate when classifying bots and 92.61% accurate when classifying non-bots. Overall, the default model is correct 93.8% of the time. Overall, the fast model is correct...

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Tracking Historical Twitter Followers: @elisewho vs. @stiles

My wife (@elisewho) and I (@stiles) had a silly social media moment yesterday when I replied to one of her tweets — despite the fact that she was sitting in an adjacent room of our Seoul apartment. USC professor Robert Hernandez (a.k.a. @webjournalist) captured it:   Among my favorite media couples are @elisewho and @stiles. pic.twitter.com/HLp3g90Tgc — Robert is in S. Korea (@webjournalist) February 12, 2018 The exchange, which we both...

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