Update README.md

README.md

@@ -47,6 +47,9 @@ The lexicon is derived from an English VAD resource, originally created by
 
 - Assigning VAD scores consistently across enriched word forms.
 
+[ArXiv](https://arxiv.org/abs/2512.05231)
+
+
 ## Motivation and Use Cases
 
 VAD annotations provide a nuanced representation of emotions in text and are widely used in sentiment analysis, emotion classification, and affective computing. While designed at the word level, the lexicon has been successfully applied to longer texts such as sentences and documents.
@@ -92,4 +95,12 @@ Each entry contains:
 
 
 ## Citation
-TBD
+@misc{goldin2025unveilingaffectivepolarizationtrends,
+      title={Unveiling Affective Polarization Trends in Parliamentary Proceedings}, 
+      author={Gili Goldin and Ella Rabinovich and Shuly Wintner},
+      year={2025},
+      eprint={2512.05231},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2512.05231}, 
+}