| Title |
Transformer-based detection of propaganda techniques in a low-resource language: a case study in Lithuanian |
| Authors |
Rizgelienė, Ieva ; Zaranka, Paulius ; Korvel, Gražina ; Marcinkevičius, Virginijus |
| DOI |
10.15388/26-INFOR633 |
| Full Text |
|
| Is Part of |
Informatica.. Vilnius : Vilniaus universiteto leidykla. 2026, first published online, p. [1-30].. ISSN 0868-4952. eISSN 1822-8844 |
| Keywords [eng] |
propaganda technique detection ; low-resource language ; transformers |
| Abstract [eng] |
Propaganda techniques are a key tool for creating misleading content, often disseminated in native languages to increase their impact. Therefore, it is increasingly important to develop detection models not only for high-resource languages but also for low-resource languages, which still face significant limitations in propaganda detection. This study presents the first approach to automated propaganda technique detection in Lithuanian using the HALT-PROP corpus. We adapt the standard framework to account for frequent overlap between techniques. Experiments with the Lithuanian transformer LT-MLKM-modernBERT show that BILOU tagging improves span identification, while sentence classification based on span-level information enhances technique detection for most techniques. The results also indicate that training separate binary classifiers is more effective than multi-label classification in this setting. Overall, the proposed approach outperforms GPT-5.3 on most techniques and provides a strong baseline for propaganda technique detection in Lithuanian. |
| Published |
Vilnius : Vilniaus universiteto leidykla |
| Type |
Journal article |
| Language |
English |
| Publication date |
2026 |
| CC license |
|
