Saved in:
| Main Author: | |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2026
|
| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.19651532 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- <p>This paper presents a systematic computational analysis of public discourse surrounding the United Kingdom's digital immigration infrastructure, focusing on the digital eVisa and the Biometric Residence Permit (BRP). We construct a corpus of 1,098 Reddit posts from seventeen communities and apply an NLP pipeline combining BERTopic-based topic modelling with a comparative evaluation of two Transformer-based emotion classifiers (GoEmotions and DistilRoBERTa). Ten coherent discourse themes are identified, with procedural friction accounting for over 55% of the corpus. We demonstrate that fine-grained emotion detection produces substantially richer policy-relevant insight than coarse classifiers, and introduce a fuzzy semantic matching layer linking discourse themes to UK legislative instruments. Results provide the first large-scale quantitative validation of concerns raised by civil society organisations about the UK's digital-by-default immigration programme.</p>