Update README.md

README.md

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-license: cc-by-sa-3.0
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+---
+license: cc-by-sa-3.0
+language:
+- en
+---
+
+## Dataset Information
+
+Information ecosystems increasingly shape how people internalize exposure to adverse digital experiences, raising concerns about the long-term consequences for *information health*. In modern search and recommendation systems, ranking and personalization policies play a central role in shaping such exposure and its long-term effects on users. To study these effects in a controlled setting, we present *FrameRef*, a large-scale dataset of 1,073,740 systematically reframed claims across five framing dimensions: *authoritative*, *consensus*, *emotional*, *prestige*, and *sensationalist*, and propose a simulation-based framework for modeling sequential information exposure and reinforcement dynamics characteristic of ranking and recommendation systems. For full details, see the accompanying paper [here](https://arxiv.org/abs/2602.15273).
+
+
+## Code Repository
+
+GitHub: https://github.com/infosenselab/frameref
+
+
+## Citing FrameRef
+
+If you use this resource in your projects, please cite the following paper.
+
+
+```bibtex
+@misc{De_Lima_FrameRef_A_Framing_2025,
+author = {De Lima, Victor and Liu, Jiqun and Yang, Grace Hui},
+doi = {10.48550/arXiv.2602.15273},
+title = {{FrameRef: A Framing Dataset and Simulation Testbed for Modeling Bounded Rational Information Health}},
+url = {https://arxiv.org/abs/2602.15273},
+year = {2025}
+}
+```
+
+