Case study

Queen's University Belfast

Creating a safer academic environment

Protecting university students and staff from targeted hate, while supporting free and open exchange.

Products used:

Moderate

Queen's University Belfast

26,032

total comments monitored

2,319

harmful comments moderated

2.3x

increase in engagement

Overview

Safeguarding students and staff

How AI moderation protects universities from hate campaigns and scams.

Universities are meant to be spaces for freely debating ideas about how the world should be. So when staff members are targeted through politically motivated misinformation campaigns, that's cause for concern.

Queen's University Belfast came to us with this problem: their newly appointed chancellor became the target of hate and conspiracy theories. Not just on online forums, but in QUB's social media comments section.

QUB wanted to safeguard their staff members by moderating these comments. This would in turn help preserve their tenor of open and respectful exchange. They simultaneously wanted to optimize the way in which they communicated with their student body, freeing their comments section from spam and student fraud. Their social media pages were intended to be a place to disseminate exciting new research to the world, and connect with their students. Their overstretched social media team needed help to make that happen. The solution: Arwen's customizable AI.

Challenge

QUB's social media accounts were receiving a growing amount of targeted hate comments. Many of them were highly specific conspiracy theories, so they were difficult to catch through simple keyword filters. QUB's social team wanted to make sure that they were only removing truly harmful comments, while allowing students to voice negativity and criticism.

Fraud comments were also clogging up their social channels, with bot accounts offering courses or services to complete students' work for them. QUB wanted these removed, while still allowing for legitimate links to resources to be shared in the comments.

This meant that out-of-the-box moderation solutions were not advanced enough at discerning unwanted comments to the level that QUB required. They needed something more customizable.

Targeted hate comments on Queen's University Belfast social media

Solution

  • Arwen used a combination of highly trained models and advanced pattern detection to identify conspiracy theories, threatening, scamming, and hate comments.
  • These models could distinguish between simple criticism or negativity, which were allowed, and targeted hate campaigns, which weren't.
  • QUB implemented these moderation settings across Facebook, Instagram, TikTok, and X.
  • Unwanted comments are now identified and immediately removed, leading to a safer, more reputable social media presence across networks.
Queen's University Belfast comment section after Arwen moderation

Results

Arwen's solution means reduced harm for QUB's staff and students. It has also transformed QUB's social media pages into more constructive online spaces, both for students and the global audience interested in their research. This in turn has had a positive impact on their engagement.

  • Since QUB switched Arwen on, it has monitored over 26,000 comments, moderating 2,319 toxic and spam comments in real time.
  • Auto-moderation has freed up QUB's team to focus on generating engagement.
  • Arwen's solution has also created a more welcoming online space, allowing students to interact with their posts more.
  • All of these factors have led to over double the amount of positive engagement on QUB's posts, transforming their pages back into a useful hub for interacting with their community.
Queen's University Belfast moderation results
“

Arwen's changed the game for us. I can't believe we didn't use it before.

Head of Digital Communications, Queen's University Belfast

Stephen Baxter-Crawford

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