TY - JOUR
T1 - ValuesML: A new multilingual dataset for values detection in news and political manifestos
AU - Scharfbillig, Mario
AU - Reitis-Münstermann, Theresa
AU - Stefanovitch, Nicolas
AU - Kiesel, Johannes
AU - Brock, Paula Schulze
AU - Sneddon, Joanne
AU - Cartier, Emmanuel
AU - Ardag, Murat
AU - Arieli, Sharon
AU - Daniel, Ella
AU - Dobewall, Henrik
AU - Karl, Johannes
AU - Krasteva, Anna
AU - Oeschger, Thomas Peter
AU - Petasis, Georgios
AU - Russo, Luana
AU - Seddone, Antonella
AU - Tamo-Larrieux, Aurelia
AU - van Herk, Hester
AU - Avcı, Nazan
AU - Bobba, Giuliano
AU - Chiron, Pierre
AU - Çoymak, Ahmet
AU - Dagioglou, Maria
AU - Katsamori, Dora
AU - Leijen, Ingmar
AU - Öney, Berna
AU - Scholz-Kuhn, Ricarda
AU - Zankina, Emilia
AU - Astor, Sandrine
AU - Auer, Petra
AU - Aulino, Livia
AU - Bardi, Anat
AU - Battaglia, Fiorella
AU - Beierlein, Constanze
AU - Benish-Weisman, Maya
AU - Christodoulou, Christina
AU - Collins, Patricia R.
AU - Coppola, Irene
AU - Dâmaso, Mafalda
AU - Morren, Meike
AU - Elizarov, Einat
AU - Erlich, Naama
AU - Ezeigwe-Ephraim, Peculiar
AU - Fischer, Ronald
AU - Gaeta, Maria Cristina
AU - Gatt, Lucilla
AU - Gerera, Noam
AU - Goldman, Sjoukje
AU - Gonthier, Frederic
AU - Habermann, Stefanie
AU - van Herk, Hester
AU - van Herk, Hester
PY - 2026/10
Y1 - 2026/10
N2 - Values are important building blocks of political ideologies and are frequently invoked in political debates. Yet, because values are abstract, understanding how they are expressed in real-world discourse, and how this varies across contexts, remains a challenge. In this paper, we introduce a large-scale, expert-annotated dataset of value expression in political text, comprising news articles and political manifestos across nine languages. The dataset is grounded in the refined theory of human values (Schwartz et al., 2012) and was developed through an iterative process of annotation guideline development, annotator training, and expert curation. Value annotations capture both the type of value expressed and its evaluative framing, distinguishing whether values are expressed as attained or constrained. The final dataset comprises 2648 texts and 74,231 sentences across nine languages. This resource enables systematic, cross-linguistic analysis of value expression in political communication and provides a benchmark for developing and evaluating computational models of value detection.
AB - Values are important building blocks of political ideologies and are frequently invoked in political debates. Yet, because values are abstract, understanding how they are expressed in real-world discourse, and how this varies across contexts, remains a challenge. In this paper, we introduce a large-scale, expert-annotated dataset of value expression in political text, comprising news articles and political manifestos across nine languages. The dataset is grounded in the refined theory of human values (Schwartz et al., 2012) and was developed through an iterative process of annotation guideline development, annotator training, and expert curation. Value annotations capture both the type of value expressed and its evaluative framing, distinguishing whether values are expressed as attained or constrained. The final dataset comprises 2648 texts and 74,231 sentences across nine languages. This resource enables systematic, cross-linguistic analysis of value expression in political communication and provides a benchmark for developing and evaluating computational models of value detection.
KW - human values
KW - Large language models (LLMs)
KW - multiple languages
KW - political communication
KW - news
KW - dataset
U2 - 10.3758/s13428-026-03092-z
DO - 10.3758/s13428-026-03092-z
M3 - Article
SN - 1554-351X
VL - 58
SP - 1
EP - 26
JO - Behavior Research Methods
JF - Behavior Research Methods
IS - 10
M1 - 276
ER -