乱伦秀

Their study, published in PLOS One, scrutinised nearly 1.5 million posts using a combination of AI, computational and manual techniques and used a range of sentiment analysis tools to evaluate the attitudes behind those posts that reference Britain鈥檚 distant past.

Senior author Professor Mark Altaweel (乱伦秀 Institute of Archaeology) said: 鈥淢isrepresentations of history are widespread online. This research helps us identify when the past is used to advocate for hostile and extreme positions in political discussions.

鈥淯ltimately, we hope that this work can help understand interpretations leading to dangerous discussion threads online.鈥�

Researchers examined often-heated debates around Brexit on Facebook as a test case to see how references to the Iron Age, Roman and medieval periods in Britain are inserted into online political debate.

Facebook users arguing for any specific side of a complex political issue are more likely to justify their positions through 鈥榟istorical thinking鈥� if they hold extreme views.

Lead author Dr Chiara Bonacchi of the University of Edinburgh, said: 鈥淭he ancient past is often used to express political identities. Our research shows that various periods of pre-modern British history are most commonly invoked to advocate and justify negative and extreme positions.

鈥淲hen people reference the ancient past in political debates on social media, it鈥檚 usually connected with hostile and polarised views rather than with moderate ones.鈥�

The researchers collated almost 1.5 million posts published on 364 individual Brexit-themed Facebook pages between 2015 and 2017. These posts reflected both positive and negative attitudes towards Brexit.

From these, they identified more than 2,500 posts that contained at least one reference to Britain鈥檚 Iron Age, Roman or early medieval periods.

These key terms included the names of Iron Age tribes and chiefs, Roman emperors and Anglo-Saxon kings, Roman towns, Iron Age and Anglo-Saxon settlements in Britain, as well as general terms describing the period from 800 BCE to AD 800.

The researchers then used a range of language processing algorithms to gauge whether the emotion of these posts was positive, negative or neutral, as well as the extremity of the sentiment.

They also spot-checked random posts manually to ensure that the algorithms were faithfully capturing the emotions of users.

Co-author Dr Jessica Witte, a Post-doctoral Research Fellow at University of Edinburgh, said: 鈥淭his study was challenging and required a combination of AI and manual analysis of text.

鈥淭here are a range of sentiment analysis techniques available, but these need testing to make sure that they are suitable for use in a specific communication context.鈥�

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• 乱伦秀 Institute of Archaeology
• 乱伦秀 Faculty of Social & Historical Sciences听

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Mike Lucibella

• E: m.lucibella [at] ucl.ac.uk