Abstract / Description of output
This study assesses whether references to the ancient past in debates about political issues on social media over-represent negative and extreme views. Using precision-recall, we test the performance of three sentiment analysis methods (VADER, TextBlob and Flair Sentiment) on a corpus of 1,478,483 posts, comments and replies published on Brexit-themed Facebook pages between 2015 and 2017. Drawing on the results of VADER and manual coding, we demonstrate that: 1) texts not containing keywords relating to the Iron Age, Roman and medieval (IARM) past are mostly neutral and 2) texts with IARM keywords express more negative and extreme sentiment than those without keywords. Our findings show that mentions of the ancient past in political discourse on multi-sided issues on social media are likely to indicate the presence of hostile and polarised opinions.
Original language | English |
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Pages (from-to) | 1-11 |
Number of pages | 11 |
Journal | PLOS ONE |
DOIs | |
Publication status | Published - 4 Sept 2024 |
Keywords / Materials (for Non-textual outputs)
- sentiment
- polarisation
- political opinions
- social media
- natural language processing
- heritage
- Iron Age
- Roman
- medieval