Twitter admits during 2016 election Trump used platform half as much as Clinton but had twice as much success. Additionally, Twitter legal counsel admits to hiding up to 48% of negative Clinton twitter content (hashtag tweets surrounding DNC and Podesta emails), yet suppressed nothing negative about candidate Donald Trump…
During testimony before the Senate Intelligence Committee, Sean J. Edgett Acting General Counsel for Twitter, Inc. delivered a 20 page opening statement (full pdf below). Within the statement attorney Edgett shared the protocol for Twitter hiding hashtags they deemed troubling in the lead-up to the 2016 election.
The volume of activity on our system is enormous: Our users generate thousands of Tweets per second, hundreds of thousands of Tweets per minute, hundreds of millions of Tweets per day. ~ Sean J Edgett, Twitter General Counsel
However, amid all the examples cited, Twitter did not “hide” any material that was negative toward candidate Donald Trump. In every example cited Twitter only took action to hide user content that was negative toward candidate Hillary Clinton. A remarkable ‘coincidence‘.
[Page #6 of Testimony ] Before the election, we also detected and took action on activity relating to hashtags that have since been reported as manifestations of efforts to interfere with the 2016 election. For example, our automated spam detection systems helped mitigate the impact of automated Tweets promoting the #PodestaEmails hashtag, which originated with Wikileaks’ publication of thousands of emails from the Clinton campaign chairman John Podesta’s Gmail account.
The core of the hashtag was propagated by Wikileaks, whose account sent out a series of 118 original Tweets containing variants on the hashtag #PodestaEmails referencing the daily installments of the emails released on the Wikileaks website.
In the two months preceding the election, around 57,000 users posted approximately 426,000 unique Tweets containing variations of the #PodestaEmails hashtag. Approximately one quarter (25%) of those Tweets received internal tags from our automation detection systems that hid them from searches.
As described in greater detail below, our systems detected and hid just under half (48%) of the Tweets relating to variants of another notable hashtag, #DNCLeak, which concerned the disclosure of leaked emails from the Democratic National Committee. (pdf link)
Additionally, according to the Twitter analysis (Page #11) their review found a negligible amount of overall activity (within the Hashtags they forcibly hid from view) came from any account with “potential” linkage to Russia:
“Slightly under 4% of Tweets containing #PodestaEmails came from accounts with potential links to Russia. […] With respect to #DNCLeak, approximately 23,000 users posted around 140,000 unique Tweets with that hashtag in the relevant period. Of those Tweets, roughly 2% were from potentially Russian-linked accounts.”
…which begs the question. This analysis was, by their own admission, “in retrospect”, meaning after the fact. There’s no way they could identify the user affiliation as it was happening. So why did they “hide” the trending hashtag?
Further, and in relationship to that question, if slightly under 4% of tweets containing #PodestaEmails came from concerning accounts, then why take the action to hide 25% of total user content including that hashtag? Similarly, if “roughly 2%” of #DNCLeak use was from concerning users, then why did they hide 48% of the trending hashtag content?
See the problem?
Essentially Twitter legal counsel is admitting here, through twisted analytic hindsight obfuscation, they censor Twitter based on their internal opinion of the content within trending hashtags.
Hilariously, the page #11 testimony also shows that Hillary Clinton used Twitter twice as much as Donald Trump – yet had half as much engagement (re-tweets).
Our data showed that, during the relevant time period, a total of 1,625 @HillaryClinton Tweets were Retweeted approximately 8.3 million times.
The 851 Tweets from the @realDonaldTrump account during this period were Retweeted more than 11 million times.