Automatically Detecting Political Viewpoints in Norwegian Text

Author:

Doan Tu MyORCID,Baumgartner DavidORCID,Kille BenjaminORCID,Gulla Jon AtleORCID

Publisher

Springer Nature Switzerland

Reference38 articles.

1. LNCS;M Borovikova,2023

2. Chin-Yew, L.: Looking for a Few Good Metrics: ROUGE and its Evaluation. In: Proceedings of the 4th NTCIR Workshops (2004)

3. Djemili, S., Longhi, J., Marinica, C., Kotzinos, D., Sarfati, G.E.: What does Twitter have to say about Ideology? In: NLP 4 CMC: Natural Language Processing for Computer-Mediated Communication/Social Media-Pre-conference Workshop at Konvens 2014. vol. 1. Universitätsverlag Hildesheim (2014)

4. Doan, T.M., Gulla, J.A.: A survey on political viewpoints identification. Online Soc. Networks Media 30 (2022). https://doi.org/10.1016/j.osnem.2022.100208

5. Doan, T.M., Kille, B., Gulla, J.A.: Using language models for classifying the party affiliation of political texts. In: Rosso, P., Basile, V., Martínez, R., Mètais, E., Meziane, F. (eds.) NLDB. LNCS, pp. 382–393. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-08473-7_35

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