manifesto-project

Model description An xlm-roberta-large model fine-tuned on ~1,7 million annotated statements contained in the Manifesto Corpus (version 2024a). The model can be used to categorize any type of text into 56 different political topics according to the Manifesto Project's coding scheme (Handbook 4). It works for all languages the xlm-roberta model is pretrained on (overview), just note that it will perform best for the 38 languages contained in the Manifesto Corpus: |||||| |------|------|------|------|------| |armenian|bosnian|bulgarian|catalan|croatian| |czech|danish|dutch|english|estonian| |finnish|french|galician|georgian|german| |greek|hebrew|hungarian|icelandic|italian| |japanese|korean|latvian|lithuanian|macedonian| |montenegrin|norwegian|polish|portuguese|romanian| |russian|serbian|slovak|slovenian|spanish| |swedish|turkish|ukrainian| | | The model was evaluated on a test set of 200,920 annotated manifesto statements. | | Accuracy | Top2Acc | Top3Acc | Precision| Recall | F1Macro | MCC | Cross-Entropy | |-------------------------------------------------------------------------------------------------------|:--------:|:--------:|:--------:|:--------:|:------:|:--------:|:---:|:-------------:| Sentence Model| 0.57 | 0.73 | 0.81 | 0.48 | 0.43 | 0.45 | 0.55| 1.47 | Context Model | 0.64 | 0.81 | 0.88 | 0.55 | 0.52 | 0.53 | 0.63| 1.15 | Burst, Tobias / Lehmann, Pola / Franzmann, Simon / Al-Gaddooa, Denise / Ivanusch, Christoph / Regel, Sven / Riethmüller, Felicia / Weßels, Bernhard / Zehnter, Lisa (2024): manifestoberta. Version 56topics.sentence.2024.1.1. Berlin: Wissenschaftszentrum Berlin für Sozialforschung (WZB) / Göttingen: Institut für Demokratieforschung (IfDem). https://doi.org/10.25522/manifesto.manifestoberta.56topics.sentence.2024.1.1

Model description An xlm-roberta-large model fine-tuned on ~1,6 million annotated statements contained in the Manifesto Corpus (version 2023a). The model can be used to categorize any type of text into 56 different political topics according to the Manifesto Project's coding scheme (Handbook 4). It works for all languages the xlm-roberta model is pretrained on (overview), just note that it will perform best for the 38 languages contained in the Manifesto Corpus: |||||| |------|------|------|------|------| |armenian|bosnian|bulgarian|catalan|croatian| |czech|danish|dutch|english|estonian| |finnish|french|galician|georgian|german| |greek|hebrew|hungarian|icelandic|italian| |japanese|korean|latvian|lithuanian|macedonian| |montenegrin|norwegian|polish|portuguese|romanian| |russian|serbian|slovak|slovenian|spanish| |swedish|turkish|ukrainian| | | The model was evaluated on a test set of 199,046 annotated manifesto statements. | | Accuracy | Top2Acc | Top3Acc | Precision| Recall | F1Macro | MCC | Cross-Entropy | |-------------------------------------------------------------------------------------------------------|:--------:|:--------:|:--------:|:--------:|:------:|:--------:|:---:|:-------------:| Sentence Model| 0.57 | 0.73 | 0.81 | 0.49 | 0.43 | 0.45 | 0.55| 1.5 | Context Model | 0.64 | 0.81 | 0.88 | 0.54 | 0.52 | 0.53 | 0.62| 1.15 | Burst, Tobias / Lehmann, Pola / Franzmann, Simon / Al-Gaddooa, Denise / Ivanusch, Christoph / Regel, Sven / Riethmüller, Felicia / Weßels, Bernhard / Zehnter, Lisa (2023): manifestoberta. Version 56topics.sentence.2023.1.1. Berlin: Wissenschaftszentrum Berlin für Sozialforschung (WZB) / Göttingen: Institut für Demokratieforschung (IfDem). https://doi.org/10.25522/manifesto.manifestoberta.56topics.sentence.2023.1.1