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Bot Sentinel: 19% of pro-Depp tweets from single-interest accounts

This report pertains specifically to activity during the trial and the weeks after. In addition to manipulating Twitter as a platform, Bot Sentinel found that anti-Amber Heard accounts also engaged in widespread harassment of women who stood up for Amber. Although it is understandable that some people would have started their first Twitter accounts in response to a major celebrity trial, a wildly disproportionate number of anti-Amber accounts are new, suggesting that there may be paid activity of some kind. Twitter trolls who went after Amber and her supporters are beginning to attack actress Evan Rachel Wood, who is soon to face off against her own abuser in court. Attacks on Evan frequently include recycling anti-Amber talking points and drawing unfavorable comparisons in order to paint both survivors as abusers. To help readers understand the scale of the problem, we have created two graphs as a visual reference. Below these, there are further specifics of the misconduct found by Bot Sentinel.



Tactics used by anti-Amber trolls include:

  • Hashtag spamming - Repeatedly posting the same content to the same anti-Amber hashtags in order to create “the false impression of overwhelming opposition to Amber Heard” and make those hashtags trend.

  • Copypasta or duplicate content - Copy/pasting content from other anti-Amber accounts to make it appear that many people shared the same opinion and affect Twitter trends.

  • Abuse and harassment - Attacking Amber supporters, often en masse and in misogynistic, coarse, and threatening terms. One troll created a fake account using the photograph of a pro-Amber academic’s dead child in order to harass her. Many Amber supporters received death threats or were doxxed (had their private information revealed, putting their safety at risk). This intimidation campaign has contributed to the dominance of disinformation on social media.

  • Purposely misspelling hashtags - Creating additional anti-Amber hashtag trends by subtly misspelling existing hashtags (for example, spamming #AmberHeardLsAnAbuser and #AmberHeardLsALiar in addition to the original tags, #AmberHeardIsAnAbuser and #AmberHeardIsALiar). This has helped keep anti-Amber trending hashtags at the top.

  • Bragging about their success in manipulating Twitter and encouraging other users to spam the hashtags.

Without these tactics, anti-Amber hashtags may not have dominated Twitter. It is also possible that pro-Amber hashtags would have been visible during the trial.

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