Months later, he brought up the comedian again, this time as a way to insult Cher:
Trump first called Rosie O’Donnell a “loser” in 2006, after the comedian mocked him on “The View.” As the panelists discussed Trump’s decision not to fire that year’s Miss USA following allegations about her drug and alcohol abuse, O’Donnell brought up his finances and criticized his multiple marriages. She called him a “snake oil salesman.”
This is what Trump said to People in response: “Rosie will rue the words she said. I’ll most likely sue her for making those false statements — and it’ll be fun. Rosie’s a loser. A real loser. I look forward to taking lots of money from my nice fat little Rosie.”
The reason Trump decided to insult O’Donnell again, in 2011, was apparently the announcement of her engagement. And thanks to Twitter, he had a platform to do so as many times as he wanted.
Trump has been tweeting like this for years — he joined the site in 2009 — and combing through the old tweets of the current Republican candidate for president is a pretty common pastime for the media and the politically interested at this point. But it’s just gotten a lot easier, thanks to a new, searchable database of every Trump tweet. The Trump Twitter Archive launched last week, and its creator plans to update it daily for the foreseeable future. It’s the first complete, searchable archive of the Republican candidate’s lengthy Twitter history.
“I am very emotionally invested in the election,” said Brendan Brown, the Boston-based programmer who created the archive after trying and failing to find something like it online. Brown was looking for a way to do something meaningful as the elections approached — he’d previously volunteered a little for the Bernie Sanders campaign during the primaries.
Brown wanted a way to highlight “the way that Donald Trump talks about people on Twitter,” he said. It’s certainly possible to get a sense of that using Twitter’s own search feature, but using their setup is a bit tough and time-consuming for the sort of deep dives Brown was imagining.
Because Twitter’s API only allows you to scrape a limited number of tweets for any given account, it wasn’t that easy for Brown to collect the full archive, going back to 2009. He ended up relying on a script to manually load all of Trump’s tweets, a process that took about an hour. He was then able to collect all those tweets in a usable format. Once that was done, Brown decided to read every single one of them.
“It was fun looking through it, but reading them wasn’t that fun. It took a full week,” Brown said. “The main thing that blew me away initially was all the different insults, and how many times.”
The archive has a search function, but its landing page features an impressive concordance of many of Trump’s favorite Twitter insults, along with a few groupings of other things Brown found interesting. According to his research, Trump called someone a “loser” 170 times (the database pulls up 177 hits for the word, but seven of those results are for tweets containing the word “closer”). Other favorite insults: “dumb” or “dumby” (162 tweets); “terrible” (142 tweets); and “stupid” (136 tweets).
But “loser,” by Brown’s count, is the insult winner for Trump.
“Haters and losers,” by the way, is an entire subset of Trump tweets. For a couple of years — between 2013 and 2015 — Trump tweeted more than 30 times about the “haters and the losers.” There were plenty of insults:
There’s also his weird habit of extending best wishes to the “haters and losers” during what appear to be a few emotionally charitable moments:
He also speculated about the “haters and losers'” reaction to a (then-fictional) run for the presidency:
The full list of “loser” tweets, by the way, is available to peruse here.
Brown encourages archive visitors to explore Trump’s tweets for themselves. But for those who would like a place to start, he’s highlighted some of his personal favorite finds. Those include Trump’s 371 tweets about “polls,” and his 91 tweets about global warming (which are usually some version of him referring to the phenomenon as “fake” or a “hoax.”)
(h/t The Atlantic)