# Refugees and Migration Framing Vocabulary (RMFV) [![CC BY-NC-SA 4.0][cc-by-nc-sa-shield]][cc-by-nc-sa] [cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/ [cc-by-nc-sa-image]: https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png [cc-by-nc-sa-shield]: https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg ## NEWS 🆕🔥 RMFV has new release! Check out the latest version at the ```main``` branch. The older branch is archived in the branch ```archive-v1```. **Update in the new version:** The dataset [MigParl](https://polmine.github.io/MigParl/) (Blätte & Leonhardt 2020) is used as an extra resource to enhance the compilation of RMFV. ## 1. About *Refugees and Migration Framing Vocabulary* (RMFV) is a German-language lexical resource which consists of dictionaries of 9 *issue frames* specifically related to the event "European Refugee Crisis" between 2014-2018 (issue frames ≈ the aspects of an event that are emphasized by the information sender). The nine categories of issue frames are from our *Refugees and Migration Framing Schema* (RMFS), a schema developed in a theory-driven fashion. Both RMFV and RMFS are presented in: > Qi Yu & Anselm Fliethmann. 2021. Frame detection in German political discourses: How far can we go without large-scale manual corpus annotation?. *Journal for Language Technology and Computational Linguistics*, 35(2): 15–31 **Contributors:** Qi Yu, Anselm Fliethmann, Fabian Cloos, Hannah Horschke, Bibiane Neisser, Clara Oppenländer ## 2. Cite RMFV Please cite the following paper when using RMFV: @article{yu2022frame, title={Frame Detection in German Political Discourses: How Far Can We Go Without Large-Scale Manual Corpus Annotation?}, volume={35}, url={https://jlcl.org/article/view/227}, DOI={10.21248/jlcl.35.2022.227}, number={2}, journal={Journal for Language Technology and Computational Linguistics}, author={Yu, Qi and Fliethmann, Anselm}, year={2022}, month={July}, pages={15–31} } ## 3. Acknowledgement This project is funded by the Deutsche Forschungsgemeinschaft (DFG – German Research Foundation) under Germany‘s Excellence Strategy – EXC-2035/1 – 390681379.