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.
They don’t sound like it is the best choice, just the best avaible one.
TLDR: They had the dataset lying around from previous (unrelated) research and can’t get new data because Facebook removed API access after the Cambridge Analytical Scandal.
"This corpus comprises Facebook pages and, within them, views representing different positions towards Brexit, with some being in favour and others against [10]. It was compiled as part of previous research [10, 11], but ethical approval for new analyses was sought and obtained in 2022 from the University of Edinburgh. We chose to analyse our existing dataset for two reasons. First, examining social media data about Brexit, a high-profile event that has been intensely studied, offers significant opportunities for comparing our findings to existing work whilst contributing to ongoing scholarship on public discourse about political phenomena. Second, in the UK and in many other countries, institutional ethics policies require researchers to acquire data in compliance with platforms’ Terms of Service (ToS) agreements. Like other major platforms including X (formerly Twitter), Instagram and TikTok, Facebook’s ToS state that data must be extracted using its application programming interface (API). Yet following the Cambridge Analytica scandal, Facebook closed its public API, making it challenging to acquire additional data from the platform. "
Quoted from part 2.1 Materials