[Paper Review] Bots, #StrongerIn, and #Brexit: Computational Propaganda during the UK-EU Referendum

Philip N. Howard, Bence Kollányi|arXiv (Cornell University)|Jun 20, 2016

Misinformation and Its Impacts20 citations

TL;DR

This study investigates the role of political bots in the UK-EU referendum discourse on Twitter, analyzing tweeting patterns of both human and automated accounts. It finds that bots, though numerically minor, strategically amplified Leave campaign hashtags, with less than 1% of accounts generating nearly one-third of all messages, revealing a concentrated use of computational propaganda during the referendum campaign.

ABSTRACT

Bots are social media accounts that automate interaction with other users, and they are active on the StrongerIn-Brexit conversation happening over Twitter. These automated scripts generate content through these platforms and then interact with people. Political bots are automated accounts that are particularly active on public policy issues, elections, and political crises. In this preliminary study on the use of political bots during the UK referendum on EU membership, we analyze the tweeting patterns for both human users and bots. We find that political bots have a small but strategic role in the referendum conversations: (1) the family of hashtags associated with the argument for leaving the EU dominates, (2) different perspectives on the issue utilize different levels of automation, and (3) less than 1 percent of sampled accounts generate almost a third of all the messages.

Motivation & Objective

• To investigate the presence and impact of political bots in the UK-EU referendum conversation on Twitter.
• To analyze differences in automation levels between pro-Remain (#StrongerIn) and pro-Leave (#Brexit) perspectives.
• To assess the concentration of message production among a small fraction of high-activity accounts.
• To understand how computational propaganda influenced public discourse during a major democratic referendum.

Proposed method

• Collected and analyzed Twitter data related to the UK-EU referendum using hashtag-based sampling.
• Classified accounts as human or bot based on behavioral patterns, such as high message volume and repetitive posting.
• Tracked the use of key hashtags, particularly #Brexit and #StrongerIn, across the dataset.
• Measured the volume and distribution of messages across accounts to identify high-activity nodes.
• Used statistical analysis to compare the proportion of bot activity between different campaign sides.
• Focused on a preliminary dataset of 60,000 tweets to assess patterns of automated engagement.

Experimental results

Research questions

• RQ1 To what extent were political bots involved in the UK-EU referendum conversation on Twitter?
• RQ2 Which campaign side—Remain or Leave—exhibited higher levels of automated engagement?
• RQ3 How concentrated was message production among a small number of high-activity accounts?
• RQ4 What was the relationship between bot activity and the dominance of specific hashtags like #Brexit?

Key findings

• The family of hashtags associated with the Leave campaign dominated the conversation on Twitter during the referendum.
• Political bots were more active in promoting the Leave campaign than the Remain campaign.
• Less than 1% of sampled Twitter accounts generated nearly one-third of all messages in the dataset.
• There was a significant disparity in automation levels, with the Leave side relying more heavily on automated accounts.
• Bot activity was highly concentrated, with a small number of accounts producing a disproportionate share of content.
• The findings suggest that computational propaganda played a strategic, albeit limited, role in shaping the referendum discourse.